【论文合集】Awesome Low Level Vision

这篇具有很好参考价值的文章主要介绍了【论文合集】Awesome Low Level Vision。希望对大家有所帮助。如果存在错误或未考虑完全的地方,请大家不吝赐教,您也可以点击"举报违法"按钮提交疑问。

Low-level和High-level任务

Low-level任务:常见的包括 Super-Resolution,denoise, deblur, dehze, low-light enhancement, deartifacts等。简单来说,是把特定降质下的图片还原成好看的图像,现在基本上用end-to-end的模型来学习这类 ill-posed问题的求解过程,客观指标主要是PSNR,SSIM,大家指标都刷的很高。目前面临以下几点问题:

  • 泛化性差,换个数据集,同种任务变现就很差。
  • 客观指标与主观感受存在,GAP。
  • 落地的问题,SOTA模型运算量很(上百G Flops),但实际不可能这么用。
  • 偏向于解决实际问题,主要是为人服务,如手机里的各类夜景模式、美化等,都会用到相关算法。
  • 市面上公司做 low-level 比较多的是手机厂商(华米OV)、安防(海康大华),相机(大疆,ISP厂商)、无人机(大疆)、视频网站(B站,快手等)。一般涉及到图像、视频增强的场景都是low-level试用的问题。


High-level任务:分类,检测,分割等。一般公开训练数据都是高品质的图像,当送入降质图像时,性能会有下降,即使网络已经经过大量的数据增强(形状,亮度,色度等变换)。真实应用场景是不可能像训练集那样完美的,采集图像的过程中会面临各种降质问题,需要两者来结合。简单来说,结合的方式分为以下几种

  • 直接在降质图像上fine-tuning
  • 先经过low-level的增强网络,再送入High-level的模型,两者分开训练
  • 将增强网络和高层模型(如分类)联合训练

目录

Low-level和High-level任务

CVPR2023-Low-Level-Vision

Image Restoration - 图像恢复

Image Reconstruction

Burst Restoration

Video Restoration

Super Resolution - 超分辨率

Image Super Resolution

Video Super Resolution

Image Rescaling - 图像缩放

Denoising - 去噪

Image Denoising

Deblurring - 去模糊

Image Deblurring

Deraining - 去雨

Dehazing - 去雾

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

Frame Interpolation - 插帧

Image Enhancement - 图像增强

Low-Light Image Enhancement

Image Matting - 图像抠图

Shadow Removal - 阴影消除

Image Compression - 图像压缩

Video Compression

Image Quality Assessment - 图像质量评价

Style Transfer - 风格迁移

Image Editing - 图像编辑

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

Image-to-Image / Image Guided

Others for image generation

Video Generation

Others

CVPR2022-Low-Level-Vision

Image Restoration - 图像恢复

Burst Restoration

Video Restoration

Hyperspectral Image Reconstruction

Super Resolution - 超分辨率

Image Super Resolution

Burst/Multi-frame Super Resolution

Video Super Resolution

Image Rescaling - 图像缩放

Denoising - 去噪

Image Denoising

BurstDenoising

Video Denoising

Deblurring - 去模糊

Image Deblurring

Video Deblurring

Deraining - 去雨

Dehazing - 去雾

Demoireing - 去摩尔纹

Frame Interpolation - 插帧

Spatial-Temporal Video Super-Resolution

Image Enhancement - 图像增强

Low-Light Image Enhancement

Image Harmonization - 图像协调

Image Completion/Inpainting - 图像修复

Video Inpainting

Image Matting - 图像抠图

Shadow Removal - 阴影消除

Relighting

Image Stitching - 图像拼接

Image Compression - 图像压缩

Video Compression

Image Quality Assessment - 图像质量评价

Image Decomposition

Style Transfer - 风格迁移

Image Editing - 图像编辑

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

Image-to-Image / Image Guided

Others for image generation

Video Generation/Synthesis

Others

NTIRE2022

Spectral Reconstruction from RGB

Perceptual Image Quality Assessment: Track 1 Full-Reference / Track 2 No-Reference

Inpainting: Track 1 Unsupervised / Track 2 Semantic

Efficient Super-Resolution

Night Photography Rendering

Super-Resolution and Quality Enhancement of Compressed Video: Track1 (Quality enhancement) / Track2 (Quality enhancement and x2 SR) / Track3 (Quality enhancement and x4 SR)

High Dynamic Range (HDR): Track 1 Low-complexity (fidelity constrain) / Track 2 Fidelity (low-complexity constrain)

Stereo Super-Resolution

Burst Super-Resolution: Track 2 Real

ECCV2022-Low-Level-Vision

Image Restoration - 图像恢复

Video Restoration

Super Resolution - 超分辨率

Image Super Resolution

Video Super Resolution

Denoising - 去噪

Image Denoising

Video Denoising

Deblurring - 去模糊

Image Deblurring

Video Deblurring

Image Decomposition

Deraining - 去雨

Dehazing - 去雾

Demoireing - 去摩尔纹

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

Image Fusion

Frame Interpolation - 插帧

Spatial-Temporal Video Super-Resolution

Image Enhancement - 图像增强

Low-Light Image Enhancement

Image Harmonization - 图像协调

Image Completion/Inpainting - 图像修复

Video Inpainting

Image Colorization - 图像上色

Image Matting - 图像抠图

Shadow Removal - 阴影消除

Image Compression - 图像压缩

Video Compression

Image Quality Assessment - 图像质量评价

Relighting/Delighting

Style Transfer - 风格迁移

Image Editing - 图像编辑

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

Image-to-Image / Image Guided

Others for image generation

Video Generation

Others

AAAI2022-Low-Level-Vision

Image Restoration - 图像恢复

Burst Restoration

Video Restoration

Super Resolution - 超分辨率

Image Super Resolution

Denoising - 去噪

Image Denoising

Video Denoising

Deblurring - 去模糊

Video Deblurring

Deraining - 去雨

Dehazing - 去雾

Demosaicing - 去马赛克

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

Image Enhancement - 图像增强

Low-Light Image Enhancement

Image Matting - 图像抠图

Shadow Removal - 阴影消除

Image Compression - 图像压缩

Image Quality Assessment - 图像质量评价

Style Transfer - 风格迁移

Image Editing - 图像编辑

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Video Generation

参考


CVPR2023-Low-Level-Vision

Image Restoration - 图像恢复

Efficient and Explicit Modelling of Image Hierarchies for Image Restoration

  • Paper: https://arxiv.org/abs/2303.00748
  • Code: GitHub - ofsoundof/GRL-Image-Restoration
  • Tags: Transformer

Learning Distortion Invariant Representation for Image Restoration from A Causality Perspective

  • Paper: https://arxiv.org/abs/2303.06859
  • Code: https://github.com/lixinustc/Casual-IRDIL

Generative Diffusion Prior for Unified Image Restoration and Enhancement

  • Paper: https://arxiv.org/abs/2304.01247
  • Code: https://github.com/Fayeben/GenerativeDiffusionPrior

Contrastive Semi-supervised Learning for Underwater Image Restoration via Reliable Bank

  • Paper: https://arxiv.org/abs/2303.09101
  • Code: https://github.com/Huang-ShiRui/Semi-UIR
  • Tags: Underwater Image Restoration

Nighttime Smartphone Reflective Flare Removal Using Optical Center Symmetry Prior

  • Paper: https://arxiv.org/abs/2303.15046
  • Code: https://github.com/ykdai/BracketFlare
  • Tags: Reflective Flare Removal

Image Reconstruction

Raw Image Reconstruction with Learned Compact Metadata

  • Paper: https://arxiv.org/abs/2302.12995
  • Code: GitHub - wyf0912/R2LCM: [CVPR 2023] Raw Image Reconstruction with Learned Compact Metadata

High-resolution image reconstruction with latent diffusion models from human brain activity

  • Paper: High-resolution image reconstruction with latent diffusion models from human brain activity | bioRxiv
  • Code: GitHub - yu-takagi/StableDiffusionReconstruction: Takagi and Nishimoto, CVPR 2023

DR2: Diffusion-based Robust Degradation Remover for Blind Face Restoration

  • Paper: https://arxiv.org/abs/2303.06885

Burst Restoration

Burstormer: Burst Image Restoration and Enhancement Transformer

  • Paper: https://arxiv.org/abs/2304.01194
  • Code: GitHub - akshaydudhane16/Burstormer

Video Restoration

Blind Video Deflickering by Neural Filtering with a Flawed Atlas

  • Paper: https://arxiv.org/abs/2303.08120
  • Code: GitHub - ChenyangLEI/All-In-One-Deflicker: [CVPR2023] Blind Video Deflickering by Neural Filtering with a Flawed Atlas
  • Tags: Deflickering

Super Resolution - 超分辨率

Image Super Resolution

Activating More Pixels in Image Super-Resolution Transformer

  • Paper: https://arxiv.org/abs/2205.04437
  • Code: https://github.com/XPixelGroup/HAT
  • Tags: Transformer

N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution

  • Paper: https://arxiv.org/abs/2211.11436
  • Code: https://github.com/rami0205/NGramSwin

Omni Aggregation Networks for Lightweight Image Super-Resolution

  • Paper:
  • Code: GitHub - Francis0625/Omni-SR: [CVPR2023] Implementation of ''Omni Aggregation Networks for Lightweight Image Super-Resolution".

OPE-SR: Orthogonal Position Encoding for Designing a Parameter-free Upsampling Module in Arbitrary-scale Image Super-Resolution

  • Paper: https://arxiv.org/abs/2303.01091

Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution

  • Paper: https://arxiv.org/abs/2303.05156

Super-Resolution Neural Operator

  • Paper: https://arxiv.org/abs/2303.02584
  • Code: https://github.com/2y7c3/Super-Resolution-Neural-Operator

Human Guided Ground-truth Generation for Realistic Image Super-resolution

  • Paper: https://arxiv.org/abs/2303.13069
  • Code: https://github.com/ChrisDud0257/PosNegGT

Implicit Diffusion Models for Continuous Super-Resolution

  • Paper: https://arxiv.org/abs/2303.16491
  • Code: https://github.com/Ree1s/IDM

Zero-Shot Dual-Lens Super-Resolution

  • Paper:
  • Code: https://github.com/XrKang/ZeDuSR

Learning Generative Structure Prior for Blind Text Image Super-resolution

  • Paper: https://arxiv.org/abs/2303.14726
  • Code: https://github.com/csxmli2016/MARCONet
  • Tags: Text SR

Guided Depth Super-Resolution by Deep Anisotropic Diffusion

  • Paper: https://arxiv.org/abs/2211.11592
  • Code: GitHub - prs-eth/Diffusion-Super-Resolution: [CVPR 2023] Guided Depth Super-Resolution by Deep Anisotropic Diffusion
  • Tags: Guided Depth SR

Video Super Resolution

Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting

  • Paper: https://arxiv.org/abs/2303.08331
  • Code: coulsonlee/STDO-CVPR2023 · GitHub

Structured Sparsity Learning for Efficient Video Super-Resolution

  • Paper: https://github.com/Zj-BinXia/SSL
  • Code: https://arxiv.org/abs/2206.07687

Image Rescaling - 图像缩放

HyperThumbnail: Real-time 6K Image Rescaling with Rate-distortion Optimization

  • Paper: https://arxiv.org/abs/2304.01064
  • Code: GitHub - AbnerVictor/HyperThumbnail: [CVPR 2023] HyperThumbnail: Real-time 6K Image Rescaling with Rate-distortion Optimization. Official implementation.

Denoising - 去噪

Image Denoising

Masked Image Training for Generalizable Deep Image Denoising

  • Paper: https://arxiv.org/abs/2303.13132
  • Code: https://github.com/haoyuc/MaskedDenoising

Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising

  • Paper: https://arxiv.org/abs/2303.14934
  • Cdoe: https://github.com/nagejacob/SpatiallyAdaptiveSSID
  • Tags: Self-Supervised

LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising

  • Paper: https://arxiv.org/abs/2304.00534
  • Code: https://github.com/Wang-XIaoDingdd/LGBPN
  • Tags: Self-Supervised

Real-time Controllable Denoising for Image and Video

  • Paper: https://arxiv.org/pdf/2303.16425.pdf

Deblurring - 去模糊

Image Deblurring

Structured Kernel Estimation for Photon-Limited Deconvolution

  • Paper: https://arxiv.org/abs/2303.03472
  • Code: https://github.com/sanghviyashiitb/structured-kernel-cvpr23

Blur Interpolation Transformer for Real-World Motion from Blur

  • Paper: https://arxiv.org/abs/2211.11423
  • Code: https://github.com/zzh-tech/BiT

Neumann Network with Recursive Kernels for Single Image Defocus Deblurring

  • Paper:
  • Code: https://github.com/csZcWu/NRKNet

Efficient Frequency Domain-based Transformers for High-Quality Image Deblurring

  • Paper: https://arxiv.org/abs/2211.12250
  • Code: GitHub - kkkls/FFTformer

Deraining - 去雨

Learning A Sparse Transformer Network for Effective Image Deraining

  • Paper: https://arxiv.org/abs/2303.11950
  • Code: https://github.com/cschenxiang/DRSformer

Dehazing - 去雾

RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors

  • Paper:
  • Code: GitHub - RQ-Wu/RIDCP_dehazing: [CVPR 2023] | RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors

Curricular Contrastive Regularization for Physics-aware Single Image Dehazing

  • Paper: https://arxiv.org/abs/2303.14218
  • Code: GitHub - YuZheng9/C2PNet: [CVPR 2023] Curricular Contrastive Regularization for Physics-aware Single Image Dehazing

Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Prior

  • Paper: https://arxiv.org/abs/2303.09757
  • Code: https://github.com/jiaqixuac/MAP-Net

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

Learning a Practical SDR-to-HDRTV Up-conversion using New Dataset and Degradation Models

  • Paper: https://arxiv.org/abs/2303.13031
  • Code: https://github.com/AndreGuo/HDRTVDM

Frame Interpolation - 插帧

Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation

  • Paper: https://arxiv.org/abs/2303.00440
  • Code: GitHub - MCG-NJU/EMA-VFI: [CVPR 2023] Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolatio

A Unified Pyramid Recurrent Network for Video Frame Interpolation

  • Paper: https://arxiv.org/abs/2211.03456
  • Code: GitHub - srcn-ivl/UPR-Net: Official implementation of our CVPR2023 paper "A Unified Pyramid Recurrent Network for Video Frame Interpolation"

BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation

  • Paper: https://arxiv.org/abs/2304.02225
  • Code: GitHub - JunHeum/BiFormer: BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation, CVPR2023

Event-based Video Frame Interpolation with Cross-Modal Asymmetric Bidirectional Motion Fields

  • Paper:
  • Code: GitHub - intelpro/CBMNet: Official repository of "Event-based Video Frame Interpolation with Cross-Modal Asymmetric Bidirectional Motion Fields", CVPR 2023 paper
  • Tags: Event-based

Event-based Blurry Frame Interpolation under Blind Exposure

  • Paper:
  • Code: GitHub - WarranWeng/EBFI-BE: Event-based Blurry Frame Interpolation under Blind Exposure, CVPR2023
  • Tags: Event-based

Joint Video Multi-Frame Interpolation and Deblurring under Unknown Exposure Time

  • Paper: https://arxiv.org/abs/2303.15043
  • Code: GitHub - shangwei5/VIDUE: Joint Video Multi-Frame Interpolation and Deblurring under Unknown Exposure Time (CVPR2023)
  • Tags: Frame Interpolation and Deblurring

Image Enhancement - 图像增强

Low-Light Image Enhancement

Learning Semantic-Aware Knowledge Guidance for Low-Light Image Enhancement

  • Paper:
  • Code: https://github.com/langmanbusi/Semantic-Aware-Low-Light-Image-Enhancement

Visibility Constrained Wide-band Illumination Spectrum Design for Seeing-in-the-Dark

  • Paper: https://arxiv.org/abs/2303.11642
  • Code: https://github.com/MyNiuuu/VCSD
  • Tags: NIR2RGB

Image Matting - 图像抠图

Referring Image Matting

  • Paper: https://arxiv.org/abs/2206.05149
  • Code: GitHub - JizhiziLi/RIM: [CVPR 2023] Referring Image Matting

Shadow Removal - 阴影消除

ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removal

  • Paper: https://arxiv.org/abs/2212.04711
  • Code: https://github.com/GuoLanqing/ShadowDiffusion

Image Compression - 图像压缩

Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger

  • Paper: https://arxiv.org/abs/2302.14677

Context-based Trit-Plane Coding for Progressive Image Compression

  • Paper: https://arxiv.org/abs/2303.05715
  • Code: https://github.com/seungminjeon-github/CTC

Learned Image Compression with Mixed Transformer-CNN Architectures

  • Paper: https://arxiv.org/abs/2303.14978
  • Code: GitHub - jmliu206/LIC_TCM

Video Compression

Neural Video Compression with Diverse Contexts

  • Paper: https://github.com/microsoft/DCVC
  • Code: https://arxiv.org/abs/2302.14402

Image Quality Assessment - 图像质量评价

Quality-aware Pre-trained Models for Blind Image Quality Assessment

  • Paper: https://arxiv.org/abs/2303.00521

Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective

  • Paper: https://arxiv.org/abs/2303.14968
  • Code: GitHub - zwx8981/LIQE

Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Method

  • Paper: https://arxiv.org/abs/2303.15166
  • Code: GitHub - Dreemurr-T/BAID

Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild

  • Paper: https://arxiv.org/abs/2304.00451

Style Transfer - 风格迁移

Fix the Noise: Disentangling Source Feature for Controllable Domain Translation

  • Paper: https://arxiv.org/abs/2303.11545
  • Code: https://github.com/LeeDongYeun/FixNoise

Neural Preset for Color Style Transfer

  • Paper: https://arxiv.org/abs/2303.13511
  • Code: https://github.com/ZHKKKe/NeuralPreset

CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer

  • Paper: https://arxiv.org/abs/2303.17867

StyleGAN Salon: Multi-View Latent Optimization for Pose-Invariant Hairstyle Transfer

  • Paper: https://arxiv.org/abs/2304.02744
  • Project: StyleGANSalon

Image Editing - 图像编辑

Imagic: Text-Based Real Image Editing with Diffusion Models

  • Paper: https://arxiv.org/abs/2210.09276

SINE: SINgle Image Editing with Text-to-Image Diffusion Models

  • Paper: https://arxiv.org/abs/2212.04489
  • Code: https://github.com/zhang-zx/SINE

CoralStyleCLIP: Co-optimized Region and Layer Selection for Image Editing

  • Paper: https://arxiv.org/abs/2303.05031

DeltaEdit: Exploring Text-free Training for Text-Driven Image Manipulation

  • Paper: https://arxiv.org/abs/2303.06285
  • Code: https://arxiv.org/abs/2303.06285

SIEDOB: Semantic Image Editing by Disentangling Object and Background

  • Paper: https://arxiv.org/abs/2303.13062
  • Code: GitHub - WuyangLuo/SIEDOB

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

Multi-Concept Customization of Text-to-Image Diffusion

  • Paper: https://arxiv.org/abs/2212.04488
  • Code: GitHub - adobe-research/custom-diffusion: Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)

GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis

  • Paper: https://arxiv.org/abs/2301.12959
  • Code: GitHub - tobran/GALIP: [CVPR2023] A faster, smaller, and better text-to-image model for large-scale training

Scaling up GANs for Text-to-Image Synthesis

  • Paper: https://arxiv.org/abs/2303.05511
  • Project: GigaGAN: Scaling up GANs for Text-to-Image Synthesis

MAGVLT: Masked Generative Vision-and-Language Transformer

  • Paper: https://arxiv.org/abs/2303.12208

Freestyle Layout-to-Image Synthesis

  • Paper: https://arxiv.org/abs/2303.14412
  • Code: GitHub - essunny310/FreestyleNet: [CVPR 2023 Highlight] Freestyle Layout-to-Image Synthesis

Variational Distribution Learning for Unsupervised Text-to-Image Generation

  • Paper: https://arxiv.org/abs/2303.16105

Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment

  • Paper: https://arxiv.org/abs/2303.17490
  • Project: Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment

Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation

  • Paper: https://arxiv.org/abs/2304.01816

Image-to-Image / Image Guided

LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data

  • Paper: https://arxiv.org/abs/2208.14889
  • Code: GitHub - KU-CVLAB/LANIT: Official repository for LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data (CVPR 2023)

Person Image Synthesis via Denoising Diffusion Model

  • Paper: https://arxiv.org/abs/2211.12500
  • Code: https://github.com/ankanbhunia/PIDM

Picture that Sketch: Photorealistic Image Generation from Abstract Sketches

  • Paper: https://arxiv.org/abs/2303.11162

Fine-Grained Face Swapping via Regional GAN Inversion

  • Paper: https://arxiv.org/abs/2211.14068
  • Code: https://github.com/e4s2022/e4s

Masked and Adaptive Transformer for Exemplar Based Image Translation

  • Paper: https://arxiv.org/abs/2303.17123
  • Code: GitHub - AiArt-HDU/MATEBIT: Source code of "Masked and Adaptive Transformer for Exemplar Based Image Translation", accepted by CVPR 2023.

Zero-shot Generative Model Adaptation via Image-specific Prompt Learning

  • Paper: https://arxiv.org/abs/2304.03119
  • Code: GitHub - Picsart-AI-Research/IPL-Zero-Shot-Generative-Model-Adaptation: [CVPR 2023] Zero-shot Generative Model Adaptation via Image-specific Prompt Learning

Others for image generation

AdaptiveMix: Robust Feature Representation via Shrinking Feature Space

  • Paper: https://arxiv.org/abs/2303.01559
  • Code: GitHub - WentianZhang-ML/AdaptiveMix: This is an official pytorch implementation of 'AdaptiveMix: Robust Feature Representation via Shrinking Feature Space' (accepted by CVPR2023).

MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis

  • Paper: https://arxiv.org/abs/2211.09117
  • Code: GitHub - LTH14/mage: A PyTorch implementation of MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis

Regularized Vector Quantization for Tokenized Image Synthesis

  • Paper: https://arxiv.org/abs/2303.06424

Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization

  • Paper:
  • Code: https://github.com/CrossmodalGroup/DynamicVectorQuantization

Not All Image Regions Matter: Masked Vector Quantization for Autoregressive Image Generation

  • Paper:
  • Code: https://github.com/CrossmodalGroup/MaskedVectorQuantization

Exploring Incompatible Knowledge Transfer in Few-shot Image Generation

  • Paper:
  • Code: GitHub - yunqing-me/RICK: The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Post-training Quantization on Diffusion Models

  • Paper: https://arxiv.org/abs/2211.15736
  • Code: GitHub - 42Shawn/PTQ4DM: Implementation of Post-training Quantization on Diffusion Models (CVPR 2023)

LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation

  • Paper: https://arxiv.org/abs/2303.17189
  • Code: GitHub - ZGCTroy/LayoutDiffusion

DiffCollage: Parallel Generation of Large Content with Diffusion Models

  • Paper: https://arxiv.org/abs/2303.17076
  • Project: DiffCollage: Parallel Generation of Large Content with Diffusion Models

Few-shot Semantic Image Synthesis with Class Affinity Transfer

  • Paper: https://arxiv.org/abs/2304.02321

Video Generation

Conditional Image-to-Video Generation with Latent Flow Diffusion Models

  • Paper: https://arxiv.org/abs/2303.13744
  • Code: GitHub - nihaomiao/CVPR23_LFDM: The pytorch implementation of our CVPR 2023 paper "Conditional Image-to-Video Generation with Latent Flow Diffusion Models"

Video Probabilistic Diffusion Models in Projected Latent Space

  • Paper: https://arxiv.org/abs/2302.07685
  • Code: https://github.com/sihyun-yu/PVDM

DPE: Disentanglement of Pose and Expression for General Video Portrait Editing

  • Paper: https://arxiv.org/abs/2301.06281
  • Code: GitHub - Carlyx/DPE: [CVPR 2023] DPE: Disentanglement of Pose and Expression for General Video Portrait Editing

Decomposed Diffusion Models for High-Quality Video Generation

  • Paper: https://arxiv.org/abs/2303.08320

Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding

  • Paper: https://arxiv.org/abs/2212.02802
  • Code: GitHub - man805/Diffusion-Video-Autoencoders: An official implementation of "Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding" (CVPR 2023) in PyTorch.

MoStGAN: Video Generation with Temporal Motion Styles

  • Paper:
  • Code: https://github.com/xiaoqian-shen/MoStGAN

Others

DC2: Dual-Camera Defocus Control by Learning to Refocus

  • Paper: https://arxiv.org/abs/2304.03285
  • Project: DC2: Dual-Camera Defocus Control by Learning to Refocus

Images Speak in Images: A Generalist Painter for In-Context Visual Learning

  • Paper: https://arxiv.org/abs/2212.02499
  • Code: https://github.com/baaivision/Painter

Unifying Layout Generation with a Decoupled Diffusion Model

  • Paper: https://arxiv.org/abs/2303.05049

Unsupervised Domain Adaption with Pixel-level Discriminator for Image-aware Layout Generation

  • Paper: https://arxiv.org/abs/2303.14377

PosterLayout: A New Benchmark and Approach for Content-aware Visual-Textual Presentation Layout

  • Paper: https://arxiv.org/abs/2303.15937
  • Code: https://github.com/PKU-ICST-MIPL/PosterLayout-CVPR2023

LayoutDM: Discrete Diffusion Model for Controllable Layout Generation

  • Paper: https://arxiv.org/abs/2303.08137
  • Code: https://github.com/CyberAgentAILab/layout-dm

Make-A-Story: Visual Memory Conditioned Consistent Story Generation

  • Paper: https://arxiv.org/abs/2211.13319
  • Code: https://github.com/ubc-vision/Make-A-Story

Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models

  • Paper: https://arxiv.org/abs/2303.10774
  • Code: mattolson93/cross_gan_auditing · GitHub

LightPainter: Interactive Portrait Relighting with Freehand Scribble

  • Paper: https://arxiv.org/abs/2303.12950
  • Tags: Portrait Relighting

Neural Texture Synthesis with Guided Correspondence

  • Paper:
  • Code: https://github.com/EliotChenKJ/Guided-Correspondence-Loss
  • Tags: Texture Synthesis

CF-Font: Content Fusion for Few-shot Font Generation

  • Paper: https://arxiv.org/abs/2303.14017
  • Code: https://github.com/wangchi95/CF-Font
  • Tags: Font Generation

DeepVecFont-v2: Exploiting Transformers to Synthesize Vector Fonts with Higher Quality

  • Paper: https://arxiv.org/abs/2303.14585
  • Code: GitHub - yizhiwang96/deepvecfont-v2: [CVPR 2023] DeepVecFont-v2: Exploiting Transformers to Synthesize Vector Fonts with Higher Quality

Handwritten Text Generation from Visual Archetypes

  • Paper: https://arxiv.org/abs/2303.15269
  • Tags: Handwriting Generation

Disentangling Writer and Character Styles for Handwriting Generation

  • Paper: https://arxiv.org/abs/2303.14736
  • Code: GitHub - dailenson/SDT: This repository is the official implementation of Disentangling Writer and Character Styles for Handwriting Generation (CVPR23).
  • Tags: Handwriting Generation

Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert

  • Paper: https://arxiv.org/abs/2303.17480
  • Code: GitHub - Sxjdwang/TalkLip

Uncurated Image-Text Datasets: Shedding Light on Demographic Bias

  • Paper: https://arxiv.org/abs/2304.02828
  • Code: https://github.com/noagarcia/phase

CVPR2022-Low-Level-Vision

Image Restoration - 图像恢复

Restormer: Efficient Transformer for High-Resolution Image Restoration

  • Paper: https://arxiv.org/abs/2111.09881
  • Code: https://github.com/swz30/Restormer
  • Tags: Transformer

Uformer: A General U-Shaped Transformer for Image Restoration

  • Paper: https://arxiv.org/abs/2106.03106
  • Code: https://github.com/ZhendongWang6/Uformer
  • Tags: Transformer

MAXIM: Multi-Axis MLP for Image Processing

  • Paper: https://arxiv.org/abs/2201.02973
  • Code: https://github.com/google-research/maxim
  • Tags: MLP, also do image enhancement

All-In-One Image Restoration for Unknown Corruption

  • Paper: http://pengxi.me/wp-content/uploads/2022/03/All-In-One-Image-Restoration-for-Unknown-Corruption.pdf
  • Code: https://github.com/XLearning-SCU/2022-CVPR-AirNet

Fourier Document Restoration for Robust Document Dewarping and Recognition

  • Paper: https://arxiv.org/abs/2203.09910
  • Tags: Document Restoration

Exploring and Evaluating Image Restoration Potential in Dynamic Scenes

  • Paper: https://arxiv.org/abs/2203.11754

ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image Prior

  • Paper: https://arxiv.org/abs/2111.15362v2
  • Code: https://github.com/ozgurkara99/ISNAS-DIP
  • Tags: DIP, NAS

Deep Generalized Unfolding Networks for Image Restoration

  • Paper: https://arxiv.org/abs/2204.13348
  • Code: https://github.com/MC-E/Deep-Generalized-Unfolding-Networks-for-Image-Restoration

Attentive Fine-Grained Structured Sparsity for Image Restoration

  • Paper: https://arxiv.org/abs/2204.12266
  • Code: https://github.com/JungHunOh/SLS_CVPR2022

Self-Supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Self-Supervised

KNN Local Attention for Image Restoration

  • Paper: CVPR 2022 Open Access Repository
  • Code: https://sites.google.com/view/cvpr22-kit

GIQE: Generic Image Quality Enhancement via Nth Order Iterative Degradation

  • Paper: CVPR 2022 Open Access Repository

TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions

  • Paper: https://arxiv.org/abs/2111.14813
  • Code: https://github.com/jeya-maria-jose/TransWeather
  • Tags: Adverse Weather

Learning Multiple Adverse Weather Removal via Two-stage Knowledge Learning and Multi-contrastive Regularization: Toward a Unified Model

  • Paper: https://openaccess.thecvf.com/content/CVPR2022/papers/Chen_Learning_Multiple_Adverse_Weather_Removal_via_Two-Stage_Knowledge_Learning_and_CVPR_2022_paper.pdf
  • Code: https://github.com/fingerk28/Two-stage-Knowledge-For-Multiple-Adverse-Weather-Removal
  • Tags: Adverse Weathe(deraining, desnowing, dehazing)

Rethinking Deep Face Restoration

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Face

RestoreFormer: High-Quality Blind Face Restoration From Undegraded Key-Value Pairs

  • Paper: CVPR 2022 Open Access Repository
  • Code: https://github.com/wzhouxiff/RestoreFormer
  • Tags: Face

Blind Face Restoration via Integrating Face Shape and Generative Priors

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Face

End-to-End Rubbing Restoration Using Generative Adversarial Networks

  • Paper: https://arxiv.org/abs/2205.03743
  • Code: https://github.com/qingfengtommy/RubbingGAN
  • Tags: [Workshop], Rubbing Restoration

GenISP: Neural ISP for Low-Light Machine Cognition

  • Paper: https://arxiv.org/abs/2205.03688
  • Tags: [Workshop], ISP

Burst Restoration

A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift

  • Paper: https://arxiv.org/abs/2203.09294
  • Code: GitHub - GuoShi28/2StageAlign: The official codes of our CVPR2022 paper: A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift
  • Tags: joint denoising and demosaicking

Burst Image Restoration and Enhancement

  • Paper: https://arxiv.org/abs/2110.03680
  • Code: https://github.com/akshaydudhane16/BIPNet

Video Restoration

Revisiting Temporal Alignment for Video Restoration

  • Paper: https://arxiv.org/abs/2111.15288
  • Code: GitHub - redrock303/Revisiting-Temporal-Alignment-for-Video-Restoration

Neural Compression-Based Feature Learning for Video Restoration

  • Paper:https://arxiv.org/abs/2203.09208

Bringing Old Films Back to Life

  • Paper: https://arxiv.org/abs/2203.17276
  • Code: https://github.com/raywzy/Bringing-Old-Films-Back-to-Life

Neural Global Shutter: Learn to Restore Video from a Rolling Shutter Camera with Global Reset Feature

  • Paper: https://arxiv.org/abs/2204.00974
  • Code: https://github.com/lightChaserX/neural-global-shutter
  • Tags: restore clean global shutter (GS) videos

Context-Aware Video Reconstruction for Rolling Shutter Cameras

  • Paper: https://arxiv.org/abs/2205.12912
  • Code: https://github.com/GitCVfb/CVR
  • Tags: Rolling Shutter Cameras

E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations

  • Paper: https://arxiv.org/abs/2206.07578
  • Tags: Event camera
  • Withdrawal due to plagiarism

Hyperspectral Image Reconstruction

Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction

  • Paper: https://arxiv.org/abs/2111.07910
  • Code: https://github.com/caiyuanhao1998/MST

HDNet: High-resolution Dual-domain Learning for Spectral Compressive Imaging

  • Paper: https://arxiv.org/abs/2203.02149

Super Resolution - 超分辨率

Image Super Resolution

Reflash Dropout in Image Super-Resolution

  • Paper: https://arxiv.org/abs/2112.12089
  • Code: https://github.com/Xiangtaokong/Reflash-Dropout-in-Image-Super-Resolution

Residual Local Feature Network for Efficient Super-Resolution

  • Paper: https://arxiv.org/abs/2205.07514
  • Code: https://github.com/fyan111/RLFN
  • Tags: won the first place in the runtime track of the NTIRE 2022 efficient super-resolution challenge

Learning the Degradation Distribution for Blind Image Super-Resolution

  • Paper: https://arxiv.org/abs/2203.04962
  • Code: GitHub - greatlog/UnpairedSR: This is an offical implementation of the CVPR2022's paper [Learning the Degradation Distribution for Blind Image Super-Resolution](https://arxiv.org/abs/2203.04962)
  • Tags: Blind SR

Deep Constrained Least Squares for Blind Image Super-Resolution

  • Paper: https://arxiv.org/abs/2202.07508
  • Code: GitHub - Algolzw/DCLS: "Deep Constrained Least Squares for Blind Image Super-Resolution", CVPR 2022.
  • Tags: Blind SR

Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel

  • Paper: https://arxiv.org/abs/2107.00986
  • Code: https://github.com/zsyOAOA/BSRDM
  • Tags: Blind SR

Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution

  • Paper: https://arxiv.org/abs/2203.09195
  • Code: https://github.com/csjliang/LDL
  • Tags: Real SR

Dual Adversarial Adaptation for Cross-Device Real-World Image Super-Resolution

  • Paper: https://arxiv.org/abs/2205.03524
  • Code: GitHub - lonelyhope/DADA
  • Tags: Real SR

LAR-SR: A Local Autoregressive Model for Image Super-Resolution

  • Paper: CVPR 2022 Open Access Repository

Texture-Based Error Analysis for Image Super-Resolution

  • Paper: CVPR 2022 Open Access Repository

Learning to Zoom Inside Camera Imaging Pipeline

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Raw-to-Raw domain

Task Decoupled Framework for Reference-Based Super-Resolution

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Reference-Based

GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors

  • Paper: https://arxiv.org/abs/2203.07319
  • Code: GitHub - hejingwenhejingwen/GCFSR
  • Tags: Face SR

A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolution

  • Paper: https://arxiv.org/abs/2203.09388
  • Code: https://github.com/mjq11302010044/TATT
  • Tags: Text SR

Learning Graph Regularisation for Guided Super-Resolution

  • Paper: https://arxiv.org/abs/2203.14297
  • Tags: Guided SR

Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution

  • Paper: https://arxiv.org/abs/2203.13963
  • Code: https://github.com/XAIMI-Lab/McMRSR
  • Tags: MRI SR

Discrete Cosine Transform Network for Guided Depth Map Super-Resolution

  • Paper: https://arxiv.org/abs/2104.06977
  • Code: https://github.com/Zhaozixiang1228/GDSR-DCTNet
  • Tags: Guided Depth Map SR

SphereSR: 360deg Image Super-Resolution With Arbitrary Projection via Continuous Spherical Image Representation

  • Paper: CVPR 2022 Open Access Repository

IMDeception: Grouped Information Distilling Super-Resolution Network

  • Paper: https://arxiv.org/abs/2204.11463
  • Tags: [Workshop], lightweight

A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds

  • Paper: https://arxiv.org/abs/2205.04910
  • Code: https://github.com/WenlongZhang0517/CloserLookBlindSR
  • Tags: [Workshop], Blind SR

Burst/Multi-frame Super Resolution

Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites

  • Paper: https://arxiv.org/abs/2205.02031
  • Code: GitHub - centreborelli/HDR-DSP-SR: Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites
  • Tags: Self-Supervised, multi-exposure

Video Super Resolution

BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment

  • Paper: https://arxiv.org/abs/2104.13371
  • Code: GitHub - ckkelvinchan/BasicVSR_PlusPlus: Official repository of "BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment"

Learning Trajectory-Aware Transformer for Video Super-Resolution

  • Paper: https://arxiv.org/abs/2204.04216
  • Code: GitHub - researchmm/TTVSR: [CVPR'22 Oral] TTVSR: Learning Trajectory-Aware Transformer for Video Super-Resolution
  • Tags: Transformer

Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modeling

  • Paper: https://arxiv.org/abs/2204.07114

Investigating Tradeoffs in Real-World Video Super-Resolution

  • Paper: https://arxiv.org/abs/2111.12704
  • Code: https://github.com/ckkelvinchan/RealBasicVSR
  • Tags: Real-world, RealBaiscVSR

Memory-Augmented Non-Local Attention for Video Super-Resolution

  • Paper: CVPR 2022 Open Access Repository

Stable Long-Term Recurrent Video Super-Resolution

  • Paper: CVPR 2022 Open Access Repository

Reference-based Video Super-Resolution Using Multi-Camera Video Triplets

  • Paper: https://arxiv.org/abs/2203.14537
  • Code: https://github.com/codeslake/RefVSR
  • Tags: Reference-based VSR

A New Dataset and Transformer for Stereoscopic Video Super-Resolution

  • Paper: https://arxiv.org/abs/2204.10039
  • Code: https://github.com/H-deep/Trans-SVSR/
  • Tags: Stereoscopic Video Super-Resolution

Image Rescaling - 图像缩放

Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence

  • Paper: https://arxiv.org/abs/2203.00911

Faithful Extreme Rescaling via Generative Prior Reciprocated Invertible Representations

  • Paper: CVPR 2022 Open Access Repository
  • Code: https://github.com/cszzx/GRAIN

Denoising - 去噪

Image Denoising

Self-Supervised Image Denoising via Iterative Data Refinement

  • Paper: https://arxiv.org/abs/2111.14358
  • Code: https://github.com/zhangyi-3/IDR
  • Tags: Self-Supervised

Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots

  • Paper: https://arxiv.org/abs/2203.06967
  • Code: https://github.com/demonsjin/Blind2Unblind
  • Tags: Self-Supervised

AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network

  • Paper: https://arxiv.org/abs/2203.11799
  • Code: https://github.com/wooseoklee4/AP-BSN
  • Tags: Self-Supervised

CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image

  • Paper: https://arxiv.org/abs/2203.13009
  • Code: GitHub - Reyhanehne/CVF-SID_PyTorch
  • Tags: Self-Supervised

Noise Distribution Adaptive Self-Supervised Image Denoising Using Tweedie Distribution and Score Matching

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Self-Supervised

Noise2NoiseFlow: Realistic Camera Noise Modeling without Clean Images

  • Paper: https://arxiv.org/abs/2206.01103
  • Tags: Noise Modeling, Normalizing Flow

Modeling sRGB Camera Noise with Normalizing Flows

  • Paper: https://arxiv.org/abs/2206.00812
  • Tags: Noise Modeling, Normalizing Flow

Estimating Fine-Grained Noise Model via Contrastive Learning

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Noise Modeling, Constrastive Learning

Multiple Degradation and Reconstruction Network for Single Image Denoising via Knowledge Distillation

  • Paper: https://arxiv.org/abs/2204.13873
  • Tags: [Workshop]

BurstDenoising

NAN: Noise-Aware NeRFs for Burst-Denoising

  • Paper: https://arxiv.org/abs/2204.04668
  • Tags: NeRFs

Video Denoising

Dancing under the stars: video denoising in starlight

  • Paper: https://arxiv.org/abs/2204.04210
  • Code: https://github.com/monakhova/starlight_denoising/
  • Tags: video denoising in starlight

Deblurring - 去模糊

Image Deblurring

Learning to Deblur using Light Field Generated and Real Defocus Images

  • Paper: https://arxiv.org/abs/2204.00367
  • Code: https://github.com/lingyanruan/DRBNet
  • Tags: Defocus deblurring

Pixel Screening Based Intermediate Correction for Blind Deblurring

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Blind

Deblurring via Stochastic Refinement

  • Paper: CVPR 2022 Open Access Repository

XYDeblur: Divide and Conquer for Single Image Deblurring

  • Paper: CVPR 2022 Open Access Repository

Unifying Motion Deblurring and Frame Interpolation with Events

  • Paper: https://arxiv.org/abs/2203.12178
  • Tags: event-based

E-CIR: Event-Enhanced Continuous Intensity Recovery

  • Paper: https://arxiv.org/abs/2203.01935
  • Code: https://github.com/chensong1995/E-CIR
  • Tags: event-based

Video Deblurring

Multi-Scale Memory-Based Video Deblurring

  • Paper: https://arxiv.org/abs/2203.01935
  • Code: https://github.com/jibo27/MemDeblur

Deraining - 去雨

Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyond

  • Paper: https://arxiv.org/abs/2203.16931
  • Code: https://github.com/yuyi-sd/Robust_Rain_Removal

Unpaired Deep Image Deraining Using Dual Contrastive Learning

  • Paper: https://arxiv.org/abs/2109.02973
  • Tags: Contrastive Learning, Unpaired

Unsupervised Deraining: Where Contrastive Learning Meets Self-similarity

  • Paper: https://arxiv.org/abs/2203.11509
  • Tags: Contrastive Learning, Unsupervised

Dreaming To Prune Image Deraining Networks

  • Paper: CVPR 2022 Open Access Repository

Dehazing - 去雾

Self-augmented Unpaired Image Dehazing via Density and Depth Decomposition

  • Paper: CVPR 2022 Open Access Repository
  • Code: https://github.com/YaN9-Y/D4
  • Tags: Unpaired

Towards Multi-Domain Single Image Dehazing via Test-Time Training

  • Paper: CVPR 2022 Open Access Repository

Image Dehazing Transformer With Transmission-Aware 3D Position Embedding

  • Paper: CVPR 2022 Open Access Repository

Physically Disentangled Intra- and Inter-Domain Adaptation for Varicolored Haze Removal

  • Paper: CVPR 2022 Open Access Repository

Demoireing - 去摩尔纹

Video Demoireing with Relation-Based Temporal Consistency

  • Paper: https://arxiv.org/abs/2204.02957
  • Code: https://github.com/CVMI-Lab/VideoDemoireing

Frame Interpolation - 插帧

ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolation

  • Paper: https://arxiv.org/abs/2111.15483
  • Code: https://github.com/danielism97/ST-MFNet

Long-term Video Frame Interpolation via Feature Propagation

  • Paper: https://arxiv.org/abs/2203.15427

Many-to-many Splatting for Efficient Video Frame Interpolation

  • Paper: https://arxiv.org/abs/2204.03513
  • Code: https://github.com/feinanshan/M2M_VFI

Video Frame Interpolation with Transformer

  • Paper: https://arxiv.org/abs/2205.07230
  • Code: https://github.com/dvlab-research/VFIformer
  • Tags: Transformer

Video Frame Interpolation Transformer

  • Paper: https://arxiv.org/abs/2111.13817
  • Code: https://github.com/zhshi0816/Video-Frame-Interpolation-Transformer
  • Tags: Transformer

IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation

  • Paper: https://arxiv.org/abs/2205.14620
  • Code: GitHub - ltkong218/IFRNet: IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation (CVPR 2022)

TimeReplayer: Unlocking the Potential of Event Cameras for Video Interpolation

  • Paper: https://arxiv.org/abs/2203.13859
  • Tags: Event Camera

Time Lens++: Event-based Frame Interpolation with Parametric Non-linear Flow and Multi-scale Fusion

  • Paper: https://arxiv.org/abs/2203.17191
  • Tags: Event-based

Unifying Motion Deblurring and Frame Interpolation with Events

  • Paper: https://arxiv.org/abs/2203.12178
  • Tags: event-based

Multi-encoder Network for Parameter Reduction of a Kernel-based Interpolation Architecture

  • Paper: https://arxiv.org/abs/2205.06723
  • Tags: [Workshop]

Spatial-Temporal Video Super-Resolution

RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution

  • Paper: https://arxiv.org/abs/2203.14186
  • Code: https://github.com/llmpass/RSTT

Spatial-Temporal Space Hand-in-Hand: Spatial-Temporal Video Super-Resolution via Cycle-Projected Mutual Learning

  • Paper: https://arxiv.org/abs/2205.05264

VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolution

  • Paper: https://arxiv.org/abs/2206.04647
  • Code: https://github.com/Picsart-AI-Research/VideoINR-Continuous-Space-Time-Super-Resolution

Image Enhancement - 图像增强

AdaInt: Learning Adaptive Intervals for 3D Lookup Tables on Real-time Image Enhancement

  • Paper: https://arxiv.org/abs/2204.13983
  • Code: https://github.com/ImCharlesY/AdaInt

Exposure Correction Model to Enhance Image Quality

  • Paper: https://arxiv.org/abs/2204.10648
  • Code: GitHub - yamand16/ExposureCorrection
  • Tags: [Workshop]

Low-Light Image Enhancement

Abandoning the Bayer-Filter to See in the Dark

  • Paper: https://arxiv.org/abs/2203.04042
  • Code: https://github.com/TCL-AILab/Abandon_Bayer-Filter_See_in_the_Dark

Toward Fast, Flexible, and Robust Low-Light Image Enhancement

  • Paper: https://arxiv.org/abs/2204.10137
  • Code: GitHub - vis-opt-group/SCI: [CVPR 2022] This is the official code for the paper "Toward Fast, Flexible, and Robust Low-Light Image Enhancement".

Deep Color Consistent Network for Low-Light Image Enhancement

  • Paper: CVPR 2022 Open Access Repository

SNR-Aware Low-Light Image Enhancement

  • Paper: CVPR 2022 Open Access Repository
  • Code: https://github.com/dvlab-research/SNR-Aware-Low-Light-Enhance

URetinex-Net: Retinex-Based Deep Unfolding Network for Low-Light Image Enhancement

  • Paper: CVPR 2022 Open Access Repository

Image Harmonization - 图像协调

High-Resolution Image Harmonization via Collaborative Dual Transformationsg

  • Paper: https://arxiv.org/abs/2109.06671
  • Code: GitHub - bcmi/CDTNet-High-Resolution-Image-Harmonization: [CVPR 2022] We unify pixel-to-pixel transformation and color-to-color transformation in a coherent framework for high-resolution image harmonization. We also release 100 high-resolution real composite images for evaluation.

SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonization

  • Paper: https://arxiv.org/abs/2204.13962
  • Code: GitHub - YCHang686/SCS-Co-CVPR2022: SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonization (CVPR 2022)

Deep Image-based Illumination Harmonization

  • Paper: https://arxiv.org/abs/2108.00150
  • Dataset: https://github.com/zhongyunbao/Dataset

Image Completion/Inpainting - 图像修复

Bridging Global Context Interactions for High-Fidelity Image Completion

  • Paper: https://arxiv.org/abs/2104.00845
  • Code: https://github.com/lyndonzheng/TFill

Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding

  • Paper: https://arxiv.org/abs/2203.00867
  • Code: GitHub - DQiaole/ZITS_inpainting: Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding (CVPR2022)

MISF: Multi-level Interactive Siamese Filtering for High-Fidelity Image Inpainting

  • Paper: https://arxiv.org/abs/2203.06304
  • Code: GitHub - tsingqguo/misf

MAT: Mask-Aware Transformer for Large Hole Image Inpainting

  • Paper: https://arxiv.org/abs/2203.15270
  • Code: GitHub - fenglinglwb/MAT: MAT: Mask-Aware Transformer for Large Hole Image Inpainting

Reduce Information Loss in Transformers for Pluralistic Image Inpainting

  • Paper: https://arxiv.org/abs/2205.05076
  • Code: GitHub - liuqk3/PUT: Paper 'Reduce Information Loss in Transformers for Pluralistic Image Inpainting' in CVPR2022

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

  • Paper: https://arxiv.org/abs/2201.09865
  • Code: GitHub - andreas128/RePaint: Official PyTorch Code and Models of "RePaint: Inpainting using Denoising Diffusion Probabilistic Models", CVPR 2022
  • Tags: DDPM

Dual-Path Image Inpainting With Auxiliary GAN Inversion

  • Paper: CVPR 2022 Open Access Repository

SaiNet: Stereo aware inpainting behind objects with generative networks

  • Paper: https://arxiv.org/abs/2205.07014
  • Tags: [Workshop]

Video Inpainting

Towards An End-to-End Framework for Flow-Guided Video Inpainting

  • Paper: https://arxiv.org/abs/2204.02663
  • Code: https://github.com/MCG-NKU/E2FGVI

The DEVIL Is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting

  • Paper: CVPR 2022 Open Access Repository
  • Code: GitHub - MichiganCOG/devil

DLFormer: Discrete Latent Transformer for Video Inpainting

  • Paper: CVPR 2022 Open Access Repository

Inertia-Guided Flow Completion and Style Fusion for Video Inpainting

  • Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Zhang_Inertia-Guided_Flow_Completion_and_Style_Fusion_for_Video_Inpainting_CVPR_2022_paper.htmll

Image Matting - 图像抠图

MatteFormer: Transformer-Based Image Matting via Prior-Tokens

  • Paper: https://arxiv.org/abs/2203.15662
  • Code: https://github.com/webtoon/matteformer

Human Instance Matting via Mutual Guidance and Multi-Instance Refinement

  • Paper: https://arxiv.org/abs/2205.10767
  • Code: GitHub - nowsyn/InstMatt: Official repository for Instance Human Matting via Mutual Guidance and Multi-Instance Refinement

Boosting Robustness of Image Matting with Context Assembling and Strong Data Augmentation

  • Paper: https://arxiv.org/abs/2201.06889

Shadow Removal - 阴影消除

Bijective Mapping Network for Shadow Removal

  • Paper: CVPR 2022 Open Access Repository

Relighting

Face Relighting with Geometrically Consistent Shadows

  • Paper: https://arxiv.org/abs/2203.16681
  • Code: GitHub - andrewhou1/GeomConsistentFR: Official Code for Face Relighting with Geometrically Consistent Shadows (CVPR 2022)
  • Tags: Face Relighting

SIMBAR: Single Image-Based Scene Relighting For Effective Data Augmentation For Automated Driving Vision Tasks

  • Paper: https://arxiv.org/abs/2204.00644

Image Stitching - 图像拼接

Deep Rectangling for Image Stitching: A Learning Baseline

  • Paper: https://arxiv.org/abs/2203.03831
  • Code: https://github.com/nie-lang/DeepRectangling

Automatic Color Image Stitching Using Quaternion Rank-1 Alignment

  • Paper: CVPR 2022 Open Access Repository

Geometric Structure Preserving Warp for Natural Image Stitching

  • Paper: CVPR 2022 Open Access Repository

Image Compression - 图像压缩

Neural Data-Dependent Transform for Learned Image Compression

  • Paper: https://arxiv.org/abs/2203.04963v1

The Devil Is in the Details: Window-based Attention for Image Compression

  • Paper: https://arxiv.org/abs/2203.08450
  • Code: https://github.com/Googolxx/STF

ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding

  • Paper: https://arxiv.org/abs/2203.10886

Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression

  • Paper: https://arxiv.org/abs/2203.10897
  • Code: GitHub - xiaosu-zhu/McQuic: Repository of CVPR'22 paper "Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression"

DPICT: Deep Progressive Image Compression Using Trit-Planes

  • Paper: https://arxiv.org/abs/2112.06334
  • Code: https://github.com/jaehanlee-mcl/DPICT

Joint Global and Local Hierarchical Priors for Learned Image Compression

  • Paper: CVPR 2022 Open Access Repository

LC-FDNet: Learned Lossless Image Compression With Frequency Decomposition Network

  • Paper: CVPR 2022 Open Access Repository

Practical Learned Lossless JPEG Recompression with Multi-Level Cross-Channel Entropy Model in the DCT Domain

  • Paper: https://arxiv.org/abs/2203.16357
  • Tags: Compress JPEG

SASIC: Stereo Image Compression With Latent Shifts and Stereo Attention

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Stereo Image Compression

Deep Stereo Image Compression via Bi-Directional Coding

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Stereo Image Compression

Learning Based Multi-Modality Image and Video Compression

  • Paper: CVPR 2022 Open Access Repository

PO-ELIC: Perception-Oriented Efficient Learned Image Coding

  • Paper: https://arxiv.org/abs/2205.14501
  • Tags: [Workshop]

Video Compression

Coarse-to-fine Deep Video Coding with Hyperprior-guided Mode Prediction

  • Paper: https://arxiv.org/abs/2206.07460

LSVC: A Learning-Based Stereo Video Compression Framework

  • Paper: CVPR 2022 Open Access Repository
  • Tags: Stereo Video Compression

Enhancing VVC with Deep Learning based Multi-Frame Post-Processing

  • Paper: https://arxiv.org/abs/2205.09458
  • Tags: [Workshop]

Image Quality Assessment - 图像质量评价

Personalized Image Aesthetics Assessment with Rich Attributes

  • Paper: https://arxiv.org/abs/2203.16754
  • Tags: Aesthetics Assessment

Incorporating Semi-Supervised and Positive-Unlabeled Learning for Boosting Full Reference Image Quality Assessment

  • Paper: https://arxiv.org/abs/2204.08763
  • Code: GitHub - happycaoyue/JSPL
  • Tags: FR-IQA

SwinIQA: Learned Swin Distance for Compressed Image Quality Assessment

  • Paper: https://arxiv.org/abs/2205.04264
  • Tags: [Workshop], compressed IQA

Image Decomposition

PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition

  • Paper: CVPR 2022 Open Access Repository
  • Code: GitHub - Morpheus3000/PIE-Net: Official model and network release for my CVPR2022 paper.

Deformable Sprites for Unsupervised Video Decomposition

  • Paper: https://arxiv.org/abs/2204.07151
  • Code: https://github.com/vye16/deformable-sprites

Style Transfer - 风格迁移

CLIPstyler: Image Style Transfer with a Single Text Condition

  • Paper: https://arxiv.org/abs/2112.00374
  • Code: GitHub - cyclomon/CLIPstyler: Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition" (CVPR 2022)
  • Tags: CLIP

Style-ERD: Responsive and Coherent Online Motion Style Transfer

  • Paper: https://arxiv.org/abs/2203.02574
  • Code: GitHub - tianxintao/Online-Motion-Style-Transfer: Code for the CVPR 2022 Paper - Style-ERD: Responsive and Coherent Online Motion Style Transfer

Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

  • Paper: https://arxiv.org/abs/2203.07740
  • Code: GitHub - YBZh/EFDM: Official PyTorch codes of CVPR2022 Oral: Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization

Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer

  • Paper: https://arxiv.org/abs/2203.13248
  • Code: https://github.com/williamyang1991/DualStyleGAN

Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation

  • Paper: https://arxiv.org/abs/2203.12835
  • Code: https://github.com/jcyang98/InST

StyTr2: Image Style Transfer With Transformers

  • Paper: CVPR 2022 Open Access Repository

PCA-Based Knowledge Distillation Towards Lightweight and Content-Style Balanced Photorealistic Style Transfer Models

  • Paper: https://arxiv.org/abs/2203.13452
  • Code: GitHub - chiutaiyin/PCA-Knowledge-Distillation: PCA-based knowledge distillation towards lightweight and content-style balanced photorealistic style transfer models

Image Editing - 图像编辑

High-Fidelity GAN Inversion for Image Attribute Editing

  • Paper: https://arxiv.org/abs/2109.06590
  • Code: https://github.com/Tengfei-Wang/HFGI

Style Transformer for Image Inversion and Editing

  • Paper: https://arxiv.org/abs/2203.07932
  • Code: https://github.com/sapphire497/style-transformer

HairCLIP: Design Your Hair by Text and Reference Image

  • Paper: https://arxiv.org/abs/2112.05142
  • Code: GitHub - wty-ustc/HairCLIP: [CVPR 2022] HairCLIP: Design Your Hair by Text and Reference Image
  • Tags: CLIP

HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing

  • Paper: https://arxiv.org/abs/2111.15666
  • Code: GitHub - yuval-alaluf/hyperstyle: Official Implementation for "HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing" (CVPR 2022) https://arxiv.org/abs/2111.15666

Blended Diffusion for Text-driven Editing of Natural Images

  • Paper: https://arxiv.org/abs/2111.14818
  • Code: GitHub - omriav/blended-diffusion: Official implementation for "Blended Diffusion for Text-driven Editing of Natural Images" [CVPR 2022]
  • Tags: CLIP, Diffusion Model

FlexIT: Towards Flexible Semantic Image Translation

  • Paper: https://arxiv.org/abs/2203.04705

SemanticStyleGAN: Learning Compositonal Generative Priors for Controllable Image Synthesis and Editing

  • Paper: https://arxiv.org/abs/2112.02236

SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches

  • Paper: https://arxiv.org/abs/2111.15078
  • Code: https://github.com/zengxianyu/sketchedit

TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing

  • Paper: https://arxiv.org/abs/2203.17266
  • Code: GitHub - BillyXYB/TransEditor: [CVPR 2022] TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing

HyperInverter: Improving StyleGAN Inversion via Hypernetwork

  • Paper: https://arxiv.org/abs/2112.00719
  • Code: GitHub - VinAIResearch/HyperInverter: HyperInverter: Improving StyleGAN Inversion via Hypernetwork (CVPR 2022)

Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing

  • Paper: https://arxiv.org/abs/2206.08357
  • Code: GitHub - adobe-research/sam_inversion: [CVPR 2022] GAN inversion and editing with spatially-adaptive multiple latent layers

Brain-Supervised Image Editing

  • Paper: CVPR 2022 Open Access Repository

SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Color Editing

  • Paper: CVPR 2022 Open Access Repository

M3L: Language-based Video Editing via Multi-Modal Multi-Level Transformers

  • Paper: https://arxiv.org/abs/2104.01122

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

Text to Image Generation with Semantic-Spatial Aware GAN

  • Paper: https://arxiv.org/abs/2104.00567
  • Code: GitHub - wtliao/text2image: Text to Image Generation with Semantic-Spatial Aware GAN

LAFITE: Towards Language-Free Training for Text-to-Image Generation

  • Paper: https://arxiv.org/abs/2111.13792
  • Code: https://github.com/drboog/Lafite

DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis

  • Paper: https://arxiv.org/abs/2008.05865
  • Code: GitHub - tobran/DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis (CVPR2022 oral)

StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis

  • Paper: https://arxiv.org/abs/2203.15799
  • Code: https://github.com/zhihengli-UR/StyleT2I

DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation

  • Paper: https://arxiv.org/abs/2110.02711
  • Code: GitHub - gwang-kim/DiffusionCLIP: [CVPR 2022] Official PyTorch Implementation for DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models

Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model

  • Paper: https://arxiv.org/abs/2111.13333
  • Code: GitHub - zipengxuc/PPE-Pytorch: Pytorch Implementation for CVPR'2022 paper ✨ "Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model"

Sound-Guided Semantic Image Manipulation

  • Paper: https://arxiv.org/abs/2112.00007
  • Code: https://github.com/kuai-lab/sound-guided-semantic-image-manipulation

ManiTrans: Entity-Level Text-Guided Image Manipulation via Token-wise Semantic Alignment and Generation

  • Paper: https://arxiv.org/abs/2204.04428

Text-to-Image Synthesis Based on Object-Guided Joint-Decoding Transformer

  • Paper: CVPR 2022 Open Access Repository

Vector Quantized Diffusion Model for Text-to-Image Synthesis

  • Paper: https://arxiv.org/abs/2111.14822

AnyFace: Free-style Text-to-Face Synthesis and Manipulation

  • Paper: https://arxiv.org/abs/2203.15334

Image-to-Image / Image Guided

Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation

  • Paper: https://arxiv.org/abs/2203.12707
  • Code: https://github.com/batmanlab/MSPC

A Style-aware Discriminator for Controllable Image Translation

  • Paper: https://arxiv.org/abs/2203.15375
  • Code: https://github.com/kunheek/style-aware-discriminator

QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation

  • Paper: https://arxiv.org/abs/2203.08483
  • Code: GitHub - sapphire497/query-selected-attention: Official implementation for "QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation" (CVPR 2022)

InstaFormer: Instance-Aware Image-to-Image Translation with Transformer

  • Paper: https://arxiv.org/abs/2203.16248

Marginal Contrastive Correspondence for Guided Image Generation

  • Paper: https://arxiv.org/abs/2204.00442
  • Code: GitHub - fnzhan/UNITE: Unbalanced Feature Transport for Exemplar-based Image Translation [CVPR 2021] and Marginal Contrastive Correspondence for Guided Image Generation [CVPR 2022]

Unsupervised Image-to-Image Translation with Generative Prior

  • Paper: https://arxiv.org/abs/2204.03641
  • Code: https://github.com/williamyang1991/GP-UNIT

Exploring Patch-wise Semantic Relation for Contrastive Learning in Image-to-Image Translation Tasks

  • Paper: https://arxiv.org/abs/2203.01532
  • Code: GitHub - jcy132/Hneg_SRC: Official Pytorch implementation of "Exploring Patch-wise Semantic Relation for Contrastive Learning in Image-to-Image Translation Tasks" (CVPR 2022)

Neural Texture Extraction and Distribution for Controllable Person Image Synthesis

  • Paper: https://arxiv.org/abs/2204.06160
  • Code: GitHub - RenYurui/Neural-Texture-Extraction-Distribution: The PyTorch implementation for paper "Neural Texture Extraction and Distribution for Controllable Person Image Synthesis" (CVPR2022 Oral)

Unpaired Cartoon Image Synthesis via Gated Cycle Mapping

  • Paper: CVPR 2022 Open Access Repository

Day-to-Night Image Synthesis for Training Nighttime Neural ISPs

  • Paper: CVPR 2022 Open Access Repository
  • Code: GitHub - SamsungLabs/day-to-night

Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint

  • Paper: CVPR 2022 Open Access Repository

Wavelet Knowledge Distillation: Towards Efficient Image-to-Image Translation

  • Paper: CVPR 2022 Open Access Repository

Self-Supervised Dense Consistency Regularization for Image-to-Image Translation

  • Paper: CVPR 2022 Open Access Repository

Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Model

  • Paper: https://arxiv.org/abs/2103.15545
  • Project Web: "Drop The GAN: In Defense of Patch Nearest Neighbors as as Single Image Generative Models
  • Tags: Image manipulation

HairMapper: Removing Hair From Portraits Using GANs

  • Paper: CVPR 2022 Open Access Repository

Others for image generation

Attribute Group Editing for Reliable Few-shot Image Generation

  • Paper: https://arxiv.org/abs/2203.08422
  • Code: https://github.com/UniBester/AGE

Modulated Contrast for Versatile Image Synthesis

  • Paper: https://arxiv.org/abs/2203.09333
  • Code: GitHub - fnzhan/MoNCE: Modulated Contrast for Versatile Image Synthesis [CVPR 2022]

Interactive Image Synthesis with Panoptic Layout Generation

  • Paper: https://arxiv.org/abs/2203.02104

Autoregressive Image Generation using Residual Quantization

  • Paper: https://arxiv.org/abs/2203.01941
  • Code: GitHub - lucidrains/RQ-Transformer: Implementation of RQ Transformer, proposed in the paper "Autoregressive Image Generation using Residual Quantization"

Dynamic Dual-Output Diffusion Models

  • Paper: https://arxiv.org/abs/2203.04304

Exploring Dual-task Correlation for Pose Guided Person Image Generation

  • Paper: https://arxiv.org/abs/2203.02910
  • Code: GitHub - PangzeCheung/Dual-task-Pose-Transformer-Network: [CVPR 2022] Exploring Dual-task Correlation for Pose Guided Person Image Generation

StyleSwin: Transformer-based GAN for High-resolution Image Generation

  • Paper: https://arxiv.org/abs/2112.10762
  • Code: GitHub - microsoft/StyleSwin: [CVPR 2022] StyleSwin: Transformer-based GAN for High-resolution Image Generation

Semantic-shape Adaptive Feature Modulation for Semantic Image Synthesis

  • Paper: https://arxiv.org/abs/2203.16898
  • Code: GitHub - cszy98/SAFM: Semantic-shape Adaptive Feature Modulation for Semantic Image Synthesis (CVPR2022)

Arbitrary-Scale Image Synthesis

  • Paper: https://arxiv.org/abs/2204.02273
  • Code: https://github.com/vglsd/ScaleParty

InsetGAN for Full-Body Image Generation

  • Paper: https://arxiv.org/abs/2203.07293

HairMapper: Removing Hair from Portraits Using GANs

  • Paper: http://www.cad.zju.edu.cn/home/jin/cvpr2022/HairMapper.pdf
  • Code: https://github.com/oneThousand1000/non-hair-FFHQ

OSSGAN: Open-Set Semi-Supervised Image Generation

  • Paper: https://arxiv.org/abs/2204.14249
  • Code: https://github.com/raven38/OSSGAN

Retrieval-based Spatially Adaptive Normalization for Semantic Image Synthesis

  • Paper: https://arxiv.org/abs/2204.02854
  • Code: GitHub - Shi-Yupeng/RESAIL-For-SIS: Retrieval-based Spatially Adaptive Normalization for Semantic Image Synthesis(CVPR2022)

A Closer Look at Few-shot Image Generation

  • Paper: https://arxiv.org/abs/2205.03805
  • Tags: Few-shot

Ensembling Off-the-shelf Models for GAN Training

  • Paper: https://arxiv.org/abs/2112.09130
  • Code: https://github.com/nupurkmr9/vision-aided-gan

Few-Shot Font Generation by Learning Fine-Grained Local Styles

  • Paper: https://arxiv.org/abs/2205.09965
  • Tags: Few-shot

Modeling Image Composition for Complex Scene Generation

  • Paper: https://arxiv.org/abs/2206.00923
  • Code: GitHub - JohnDreamer/TwFA

Global Context With Discrete Diffusion in Vector Quantised Modelling for Image Generation

  • Paper: https://arxiv.org/abs/2112.01799

Self-supervised Correlation Mining Network for Person Image Generation

  • Paper: https://arxiv.org/abs/2111.13307

Learning To Memorize Feature Hallucination for One-Shot Image Generation

  • Paper: CVPR 2022 Open Access Repository

Local Attention Pyramid for Scene Image Generation

  • Paper: CVPR 2022 Open Access Repository

High-Resolution Image Synthesis with Latent Diffusion Models

  • Paper: https://arxiv.org/abs/2112.10752
  • Code: GitHub - CompVis/latent-diffusion: High-Resolution Image Synthesis with Latent Diffusion Models

Cluster-guided Image Synthesis with Unconditional Models

  • Paper: https://arxiv.org/abs/2112.12911

SphericGAN: Semi-Supervised Hyper-Spherical Generative Adversarial Networks for Fine-Grained Image Synthesis

  • Paper: CVPR 2022 Open Access Repository

DPGEN: Differentially Private Generative Energy-Guided Network for Natural Image Synthesis

  • Paper: CVPR 2022 Open Access Repository

DO-GAN: A Double Oracle Framework for Generative Adversarial Networks

  • Paper: https://openaccess.thecvf.com/content/CVPR2022/html/Aung_DO-GAN_A_Double_Oracle_Framework_for_Generative_Adversarial_Networks_CVPR_2022_paper.html

Improving GAN Equilibrium by Raising Spatial Awareness

  • Paper: https://arxiv.org/abs/2112.00718
  • Code: https://github.com/genforce/eqgan-sa

**Polymorphic-GAN: Generating Aligned Samples Across Multiple Domains With Learned Morph Maps **

  • Paper: CVPR 2022 Open Access Repository

Manifold Learning Benefits GANs

  • Paper: https://arxiv.org/abs/2112.12618

Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data

  • Paper: https://arxiv.org/abs/2204.04950
  • Code: GitHub - FriedRonaldo/Primitives-PS: Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data - Official PyTorch Implementation (CVPR 2022)

On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models

  • Paper: https://arxiv.org/abs/2205.03859
  • Tags: [Workshop]

Generate and Edit Your Own Character in a Canonical View

  • Paper: https://arxiv.org/abs/2205.02974
  • Tags: [Workshop]

StyLandGAN: A StyleGAN based Landscape Image Synthesis using Depth-map

  • Paper: https://arxiv.org/abs/2205.06611
  • Tags: [Workshop]

Overparameterization Improves StyleGAN Inversion

  • Paper: https://arxiv.org/abs/2205.06304
  • Tags: [Workshop]

Video Generation/Synthesis

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning

  • Paper: https://arxiv.org/abs/2203.02573
  • Code: https://github.com/snap-research/MMVID

Playable Environments: Video Manipulation in Space and Time

  • Paper: https://arxiv.org/abs/2203.01914
  • Code: https://github.com/willi-menapace/PlayableEnvironments

StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2

  • Paper: https://kaust-cair.s3.amazonaws.com/stylegan-v/stylegan-v-paper.pdf
  • Code: https://github.com/universome/stylegan-v

Thin-Plate Spline Motion Model for Image Animation

  • Paper: https://arxiv.org/abs/2203.14367
  • Code: GitHub - yoyo-nb/Thin-Plate-Spline-Motion-Model: [CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.

Make It Move: Controllable Image-to-Video Generation with Text Descriptions

  • Paper: https://arxiv.org/abs/2112.02815
  • Code: GitHub - Youncy-Hu/MAGE: Make It Move: Controllable Image-to-Video Generation with Text Descriptions

Diverse Video Generation from a Single Video

  • Paper: https://arxiv.org/abs/2205.05725
  • Tags: [Workshop]

Others

GAN-Supervised Dense Visual Alignment

  • Paper: https://arxiv.org/abs/2112.05143
  • Code: https://github.com/wpeebles/gangealing

ClothFormer:Taming Video Virtual Try-on in All Module

  • Paper: https://arxiv.org/abs/2204.12151
  • Tags: Video Virtual Try-on

Iterative Deep Homography Estimation

  • Paper: https://arxiv.org/abs/2203.15982
  • Code: GitHub - imdumpl78/IHN: This is the open source implementation of the CVPR2022 paper "Iterative Deep Homography Estimation"

Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization

  • Paper: https://openaccess.thecvf.com/content/CVPR2022/papers/Li_Style-Structure_Disentangled_Features_and_Normalizing_Flows_for_Diverse_Icon_Colorization_CVPR_2022_paper.pdf
  • Code: GitHub - djosix/IconFlow: Code for "Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization", CVPR 2022.

Unsupervised Homography Estimation with Coplanarity-Aware GAN

  • Paper: https://arxiv.org/abs/2205.03821
  • Code: GitHub - megvii-research/HomoGAN: This is the official implementation of HomoGAN, CVPR2022

Diverse Image Outpainting via GAN Inversion

  • Paper: https://arxiv.org/abs/2104.00675
  • Code: GitHub - yccyenchicheng/InOut: Diverse Image Outpainting via GAN Inversion

On Aliased Resizing and Surprising Subtleties in GAN Evaluation

  • Paper: https://arxiv.org/abs/2104.11222
  • Code: GitHub - GaParmar/clean-fid: PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]

Patch-wise Contrastive Style Learning for Instagram Filter Removal

  • Paper: https://arxiv.org/abs/2204.07486
  • Code: GitHub - birdortyedi/cifr-pytorch
  • Tags: [Workshop]

NTIRE2022

New Trends in Image Restoration and Enhancement workshop and challenges on image and video processing.

Spectral Reconstruction from RGB

MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction

  • Paper: https://arxiv.org/abs/2204.07908
  • Code: GitHub - caiyuanhao1998/MST-plus-plus: "MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction" (CVPRW 2022) & (Winner of NTIRE 2022 Spectral Recovery Challenge) and a toolbox for spectral reconstruction
  • Tags: 1st place

Perceptual Image Quality Assessment: Track 1 Full-Reference / Track 2 No-Reference

MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

  • Paper: https://arxiv.org/abs/2204.08958
  • Code: GitHub - IIGROUP/MANIQA: [CVPRW 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
  • Tags: 1st place for track2

Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network

  • Paper: https://arxiv.org/abs/2204.10485
  • Code: GitHub - IIGROUP/AHIQ: [CVPRW 2022] Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network
  • Tags: 1st place for track1

MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusion

  • Paper: https://arxiv.org/abs/2205.10101
  • Tags: 2nd place in track2

Conformer and Blind Noisy Students for Improved Image Quality Assessment

  • Paper: https://arxiv.org/abs/2204.12819

Inpainting: Track 1 Unsupervised / Track 2 Semantic

GLaMa: Joint Spatial and Frequency Loss for General Image Inpainting

  • Paper: https://arxiv.org/abs/2205.07162
  • Tags: ranked first in terms of PSNR, LPIPS and SSIM in the track1

Efficient Super-Resolution

  • Report: https://arxiv.org/abs/2205.05675

ShuffleMixer: An Efficient ConvNet for Image Super-Resolution

  • Paper: https://arxiv.org/abs/2205.15175
  • Code: https://github.com/sunny2109/MobileSR-NTIRE2022
  • Tags: Winner of the model complexity track

Edge-enhanced Feature Distillation Network for Efficient Super-Resolution

  • Paper: https://arxiv.org/abs/2204.08759
  • Code: https://github.com/icandle/EFDN

Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution

  • Paper: https://arxiv.org/abs/2204.08759
  • Code: GitHub - NJU-Jet/FMEN: Lowest memory consumption and second shortest runtime in NTIRE 2022 challenge on Efficient Super-Resolution
  • Tags: Lowest memory consumption and second shortest runtime

Blueprint Separable Residual Network for Efficient Image Super-Resolution

  • Paper: https://arxiv.org/abs/2205.05996
  • Code: GitHub - xiaom233/BSRN: Blueprint Separable Residual Network for Efficient Image Super-Resolution
  • Tags: 1st place in model complexity track

Night Photography Rendering

Rendering Nighttime Image Via Cascaded Color and Brightness Compensation

  • Paper: https://arxiv.org/abs/2204.08970
  • Code: GitHub - NJUVISION/CBUnet: Official code of the "Rendering Nighttime Image Via Cascaded Color and Brightness Compensation"
  • Tags: 2nd place

Super-Resolution and Quality Enhancement of Compressed Video: Track1 (Quality enhancement) / Track2 (Quality enhancement and x2 SR) / Track3 (Quality enhancement and x4 SR)

  • Report: https://arxiv.org/abs/2204.09314
  • Homepage: GitHub - RenYang-home/NTIRE22_VEnh_SR

Progressive Training of A Two-Stage Framework for Video Restoration

  • Paper: https://arxiv.org/abs/2204.09924
  • Code: GitHub - ryanxingql/winner-ntire22-vqe: Our method and experience of wining the NTIRE22 challenge on video quality enhancement
  • Tags: 1st place in track1 and track2, 2nd place in track3

High Dynamic Range (HDR): Track 1 Low-complexity (fidelity constrain) / Track 2 Fidelity (low-complexity constrain)

  • Report: https://arxiv.org/abs/2205.12633

Efficient Progressive High Dynamic Range Image Restoration via Attention and Alignment Network

  • Paper: https://arxiv.org/abs/2204.09213
  • Tags: 2nd palce of both two tracks

Stereo Super-Resolution

  • Report: https://arxiv.org/abs/2204.09197

Parallel Interactive Transformer

  • Code: GitHub - chaineypung/CVPR-NTIRE2022-Parallel-Interactive-Transformer: This is the source code of the 7th place solution for stereo image super resolution task in 2022 CVPR NTIRE challenge.
  • Tags: 7st place

Burst Super-Resolution: Track 2 Real

BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment

  • Code: https://github.com/Algolzw/BSRT
  • Tags: 1st place

ECCV2022-Low-Level-Vision

Image Restoration - 图像恢复

Simple Baselines for Image Restoration

  • Paper: https://arxiv.org/abs/2204.04676
  • Code: https://github.com/megvii-research/NAFNet

D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration

  • Paper: https://arxiv.org/abs/2207.03294
  • Code: https://github.com/zhaoyuzhi/D2HNet

Seeing Far in the Dark with Patterned Flash

  • Paper: https://arxiv.org/abs/2207.12570
  • Code: https://github.com/zhsun0357/Seeing-Far-in-the-Dark-with-Patterned-Flash

BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks

  • Paper: https://arxiv.org/abs/2207.06873
  • Code: https://github.com/ExplainableML/BayesCap

Improving Image Restoration by Revisiting Global Information Aggregation

  • Paper: https://arxiv.org/abs/2112.04491
  • Code: https://github.com/megvii-research/TLC

Fast Two-step Blind Optical Aberration Correction

  • Paper: https://arxiv.org/abs/2208.00950
  • Code: https://github.com/teboli/fast_two_stage_psf_correction
  • Tags: Optical Aberration Correction

VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder

  • Paper: https://arxiv.org/abs/2205.06803
  • Code: https://github.com/TencentARC/VQFR
  • Tags: Blind Face Restoration

RAWtoBit: A Fully End-to-end Camera ISP Network

  • Paper: https://arxiv.org/abs/2208.07639
  • Tags: ISP and Image Compression

Transform your Smartphone into a DSLR Camera: Learning the ISP in the Wild

  • Paper: https://arxiv.org/abs/2203.10636
  • Code: https://github.com/4rdhendu/TransformPhone2DSLR
  • Tags: ISP

Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model

  • Paper: https://arxiv.org/abs/2207.10040
  • Code: https://github.com/VITA-Group/TurbNet
  • Tags: Atmospheric Turbulence Mitigation, Transformer

Modeling Mask Uncertainty in Hyperspectral Image Reconstruction

  • Paper: https://arxiv.org/abs/2112.15362
  • Code: https://github.com/Jiamian-Wang/mask_uncertainty_spectral_SCI
  • Tags: Hyperspectral Image Reconstruction

TAPE: Task-Agnostic Prior Embedding for Image Restoration

  • Paper: ECVA | European Computer Vision Association

DRCNet: Dynamic Image Restoration Contrastive Network

  • Paper: ECVA | European Computer Vision Association

ART-SS: An Adaptive Rejection Technique for Semi-Supervised Restoration for Adverse Weather-Affected Images

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/rajeevyasarla/ART-SS
  • Tags: Adverse Weather

Spectrum-Aware and Transferable Architecture Search for Hyperspectral Image Restoration

  • Paper: ECVA | European Computer Vision Association
  • Tags: Hyperspectral Image Restoration

Seeing through a Black Box: Toward High-Quality Terahertz Imaging via Subspace-and-Attention Guided Restoration

  • Paper: ECVA | European Computer Vision Association
  • Tags: Terahertz Imaging

JPEG Artifacts Removal via Contrastive Representation Learning

  • Paper: ECVA | European Computer Vision Association
  • Tags: JPEG Artifacts Removal

Zero-Shot Learning for Reflection Removal of Single 360-Degree Image

  • Paper: ECVA | European Computer Vision Association
  • Tags: Reflection Removal

Overexposure Mask Fusion: Generalizable Reverse ISP Multi-Step Refinement

  • Paper: https://arxiv.org/abs/2210.11511
  • Code: https://github.com/SenseBrainTech/overexposure-mask-reverse-ISP
  • Tagss: [Workshop], Reversed ISP

Video Restoration

Video Restoration Framework and Its Meta-Adaptations to Data-Poor Conditions

  • Paper: ECVA | European Computer Vision Association

Super Resolution - 超分辨率

Image Super Resolution

ARM: Any-Time Super-Resolution Method

  • Paper: https://arxiv.org/abs/2203.10812
  • Code: https://github.com/chenbong/ARM-Net

Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks

  • Paper: https://arxiv.org/abs/2203.03844
  • Code: https://github.com/zysxmu/DDTB

CADyQ : Contents-Aware Dynamic Quantization for Image Super Resolution

  • Paper: https://arxiv.org/abs/2207.10345
  • Code: https://github.com/Cheeun/CADyQ

Image Super-Resolution with Deep Dictionary

  • Paper: https://arxiv.org/abs/2207.09228
  • Code: https://github.com/shuntama/srdd

Perception-Distortion Balanced ADMM Optimization for Single-Image Super-Resolution

  • Paper: https://arxiv.org/abs/2208.03324
  • Code: https://github.com/Yuehan717/PDASR

Adaptive Patch Exiting for Scalable Single Image Super-Resolution

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/littlepure2333/APE

Learning Series-Parallel Lookup Tables for Efficient Image Super-Resolution

  • Paper: https://arxiv.org/abs/2207.12987
  • Code: https://github.com/zhjy2016/SPLUT
  • Tags: Efficient

MuLUT: Cooperating Mulitple Look-Up Tables for Efficient Image Super-Resolution

  • Paper: https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136780234.pdf
  • Code: https://github.com/ddlee-cn/MuLUT
  • Tags: Efficient

Efficient Long-Range Attention Network for Image Super-resolution

  • Paper: https://arxiv.org/abs/2203.06697
  • Code: https://github.com/xindongzhang/ELAN

Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution

  • Paper: https://arxiv.org/abs/2207.12577
  • Code: https://github.com/wuyushuwys/compiler-aware-nas-sr

Restore Globally, Refine Locally: A Mask-Guided Scheme to Accelerate Super-Resolution Networks

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/huxiaotaostasy/MGA-scheme

Learning Mutual Modulation for Self-Supervised Cross-Modal Super-Resolution

  • Paper: https://arxiv.org/abs/2207.09156
  • Code: https://github.com/palmdong/MMSR
  • Tags: Self-Supervised

Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed Observations

  • Paper: https://arxiv.org/abs/2203.01325
  • Code: https://github.com/cszhilu1998/SelfDZSR
  • Tags: Self-Supervised, Reference-based

Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution

  • Paper: http://www4.comp.polyu.edu.hk/~cslzhang/paper/ECCV2022_DASR.pdf
  • Code: https://github.com/csjliang/DASR
  • Tags: Real-World

D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution

  • Paper: https://arxiv.org/abs/2103.14373
  • Code: https://github.com/megvii-research/D2C-SR
  • Tag: Real-World

MM-RealSR: Metric Learning based Interactive Modulation for Real-World Super-Resolution

  • Paper: https://arxiv.org/abs/2205.05065
  • Code: https://github.com/TencentARC/MM-RealSR
  • Tag: Real-World

KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution

  • Paper: https://arxiv.org/abs/2209.10305
  • Code: https://github.com/jiahong-fu/KXNet
  • Tags: Blind

From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution

  • Paper: https://arxiv.org/abs/2210.00752
  • Code: https://github.com/csxmli2016/ReDegNet
  • Tags: Blind

Unfolded Deep Kernel Estimation for Blind Image Super-Resolution

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/natezhenghy/UDKE
  • Tags: Blind

Uncertainty Learning in Kernel Estimation for Multi-stage Blind Image Super-Resolution

  • Paper: ECVA | European Computer Vision Association
  • Tags: Blind

Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images

  • Paper: https://arxiv.org/abs/2210.04198
  • Code: https://github.com/HaomingCai/SRPO
  • Tags: Rasterized Images

Reference-based Image Super-Resolution with Deformable Attention Transformer

  • Paper: https://arxiv.org/abs/2207.11938
  • Code: https://github.com/caojiezhang/DATSR
  • Tags: Reference-based, Transformer

RRSR:Reciprocal Reference-Based Image Super-Resolution with Progressive Feature Alignment and Selection

  • Paper: ECVA | European Computer Vision Association
  • Tags: Reference-based

Boosting Event Stream Super-Resolution with a Recurrent Neural Network

  • Paper: ECVA | European Computer Vision Association
  • Tags: Event

HST: Hierarchical Swin Transformer for Compressed Image Super-resolution

  • Paper: https://arxiv.org/abs/2208.09885
  • Tags: [Workshop-AIM2022]

Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration

  • Paper: https://arxiv.org/abs/2209.11345
  • Code: https://github.com/mv-lab/swin2sr
  • Tags: [Workshop-AIM2022]

Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution

  • Paper: https://arxiv.org/abs/2208.11609
  • Code: https://github.com/Algolzw/NCNet
  • Tags: [Workshop-AIM2022]

Video Super Resolution

Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution

  • Paper: https://arxiv.org/abs/2208.03012
  • Code: https://github.com/researchmm/FTVSR
  • Tags: Compressed Video SR

A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolution

  • Paper: ECVA | European Computer Vision Association
  • Tags: Compressed Video SR

Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark Dataset

  • Paper: https://arxiv.org/abs/2209.12475
  • Code: https://github.com/zmzhang1998/Real-RawVSR

Denoising - 去噪

Image Denoising

Deep Semantic Statistics Matching (D2SM) Denoising Network

  • Paper: https://arxiv.org/abs/2207.09302
  • Code: https://github.com/MKFMIKU/d2sm

Fast and High Quality Image Denoising via Malleable Convolution

  • Paper: ECVA | European Computer Vision Association

Video Denoising

Unidirectional Video Denoising by Mimicking Backward Recurrent Modules with Look-ahead Forward Ones

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/nagejacob/FloRNN

TempFormer: Temporally Consistent Transformer for Video Denoising

  • Paper: ECVA | European Computer Vision Association
  • Tags: Transformer

Deblurring - 去模糊

Image Deblurring

Learning Degradation Representations for Image Deblurring

  • Paper: https://arxiv.org/abs/2208.05244
  • Code: https://github.com/dasongli1/Learning_degradation

Stripformer: Strip Transformer for Fast Image Deblurring

  • Paper: ECVA | European Computer Vision Association
  • Tags: Transformer

Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance

  • Paper: https://arxiv.org/abs/2207.10123
  • Code: https://github.com/zzh-tech/Animation-from-Blur
  • Tags: recovering detailed motion from a single motion-blurred image

United Defocus Blur Detection and Deblurring via Adversarial Promoting Learning

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/wdzhao123/APL
  • Tags: Defocus Blur

Realistic Blur Synthesis for Learning Image Deblurring

  • Paper: ECVA | European Computer Vision Association
  • Tags: Blur Synthesis

Event-based Fusion for Motion Deblurring with Cross-modal Attention

  • Paper:https://arxiv.org/abs/2112.00167
  • Code: https://github.com/AHupuJR/EFNet
  • Tags: Event-based

Event-Guided Deblurring of Unknown Exposure Time Videos

  • Paper: ECVA | European Computer Vision Association
  • Tags: Event-based

Video Deblurring

Spatio-Temporal Deformable Attention Network for Video Deblurring

  • Paper: https://arxiv.org/abs/2207.10852
  • Code: https://github.com/huicongzhang/STDAN

Efficient Video Deblurring Guided by Motion Magnitude

  • Paper: https://arxiv.org/abs/2207.13374
  • Code: https://github.com/sollynoay/MMP-RNN

ERDN: Equivalent Receptive Field Deformable Network for Video Deblurring

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/TencentCloud/ERDN

DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting

  • Paper: https://arxiv.org/abs/2111.09985
  • Code: https://github.com/JihyongOh/DeMFI
  • Tags: Joint Deblurring and Frame Interpolation

Towards Real-World Video Deblurring by Exploring Blur Formation Process

  • Paper: https://arxiv.org/abs/2208.13184
  • Tags: [Workshop-AIM2022]

Image Decomposition

Blind Image Decomposition

  • Paper: https://arxiv.org/abs/2108.11364
  • Code: https://github.com/JunlinHan/BID

Deraining - 去雨

Not Just Streaks: Towards Ground Truth for Single Image Deraining

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/UCLA-VMG/GT-RAIN

Rethinking Video Rain Streak Removal: A New Synthesis Model and a Deraining Network with Video Rain Prior

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/wangshauitj/RDD-Net

Dehazing - 去雾

Frequency and Spatial Dual Guidance for Image Dehazing

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/yuhuUSTC/FSDGN

Perceiving and Modeling Density for Image Dehazing

  • Paper: https://arxiv.org/abs/2111.09733
  • Code: https://github.com/Owen718/ECCV22-Perceiving-and-Modeling-Density-for-Image-Dehazing

Boosting Supervised Dehazing Methods via Bi-Level Patch Reweighting

  • Paper: ECVA | European Computer Vision Association

Unpaired Deep Image Dehazing Using Contrastive Disentanglement Learning

  • Paper: ECVA | European Computer Vision Association

Demoireing - 去摩尔纹

Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing

  • Paper: https://arxiv.org/abs/2207.09935
  • Code: https://github.com/XinYu-Andy/uhdm-page

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

Exposure-Aware Dynamic Weighted Learning for Single-Shot HDR Imaging

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/viengiaan/EDWL

Ghost-free High Dynamic Range Imaging with Context-aware Transformer

  • Paper: https://arxiv.org/abs/2208.05114
  • Code: https://github.com/megvii-research/HDR-Transformer

Selective TransHDR: Transformer-Based Selective HDR Imaging Using Ghost Region Mask

  • Paper: ECVA | European Computer Vision Association

HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields

  • Paper: https://arxiv.org/abs/2208.06787
  • Code: https://github.com/postech-ami/HDR-Plenoxels

Towards Real-World HDRTV Reconstruction: A Data Synthesis-Based Approach

  • Paper: ECVA | European Computer Vision Association

Image Fusion

FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion

  • Paper: https://arxiv.org/abs/2209.11277

Recurrent Correction Network for Fast and Efficient Multi-modality Image Fusion

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/MisakiCoca/ReCoNet

Neural Image Representations for Multi-Image Fusion and Layer Separation

  • Paper: https://arxiv.org/abs/2108.01199
  • Code: Seonghyeon Nam | Neural Image Representations for Multi-Image Fusion and Layer Separation

Fusion from Decomposition: A Self-Supervised Decomposition Approach for Image Fusion

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/erfect2020/DecompositionForFusion

Frame Interpolation - 插帧

Real-Time Intermediate Flow Estimation for Video Frame Interpolation

  • Paper: https://arxiv.org/abs/2011.06294
  • Code: https://github.com/hzwer/ECCV2022-RIFE

FILM: Frame Interpolation for Large Motion

  • Paper: https://arxiv.org/abs/2202.04901
  • Code: https://github.com/google-research/frame-interpolation

Video Interpolation by Event-driven Anisotropic Adjustment of Optical Flow

  • Paper: https://arxiv.org/abs/2208.09127

Learning Cross-Video Neural Representations for High-Quality Frame Interpolation

  • Paper: ECVA | European Computer Vision Association

Deep Bayesian Video Frame Interpolation

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/Oceanlib/DBVI

A Perceptual Quality Metric for Video Frame Interpolation

  • Paper: https://arxiv.org/abs/2210.01879
  • Code: https://github.com/hqqxyy/VFIPS

DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting

  • Paper: https://arxiv.org/abs/2111.09985
  • Code: https://github.com/JihyongOh/DeMFI
  • Tags: Joint Deblurring and Frame Interpolation

Spatial-Temporal Video Super-Resolution

Towards Interpretable Video Super-Resolution via Alternating Optimization

  • Paper: https://arxiv.org/abs/2207.10765
  • Code: https://github.com/caojiezhang/DAVSR

Image Enhancement - 图像增强

Local Color Distributions Prior for Image Enhancement

  • Paper: https://www.cs.cityu.edu.hk/~rynson/papers/eccv22b.pdf
  • Code: https://github.com/hywang99/LCDPNet

SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancement

  • Paper: https://arxiv.org/abs/2207.08351

Neural Color Operators for Sequential Image Retouching

  • Paper: https://arxiv.org/abs/2207.08080
  • Code: https://github.com/amberwangyili/neurop

Deep Fourier-Based Exposure Correction Network with Spatial-Frequency Interaction

  • Paper: ECVA | European Computer Vision Association
  • Tags: Exposure Correction

Uncertainty Inspired Underwater Image Enhancement

  • Paper: ECVA | European Computer Vision Association
  • Tags: Underwater Image Enhancement

NEST: Neural Event Stack for Event-Based Image Enhancement

  • Paper: ECVA | European Computer Vision Association
  • Tags: Event-Based

Low-Light Image Enhancement

LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

  • Paper: https://arxiv.org/abs/2202.03373
  • Code: https://github.com/sczhou/LEDNet

Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression

  • Paper: https://arxiv.org/abs/2207.10564
  • Code: https://github.com/jinyeying/night-enhancement

Image Harmonization - 图像协调

Harmonizer: Learning to Perform White-Box Image and Video Harmonization

  • Paper: https://arxiv.org/abs/2207.01322
  • Code: https://github.com/ZHKKKe/Harmonizer

DCCF: Deep Comprehensible Color Filter Learning Framework for High-Resolution Image Harmonization

  • Paper: https://arxiv.org/abs/2207.04788
  • Code: https://github.com/rockeyben/DCCF

Semantic-Guided Multi-Mask Image Harmonization

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/XuqianRen/Semantic-guided-Multi-mask-Image-Harmonization

Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization

  • Paper: https://arxiv.org/abs/2109.05750
  • Code: https://github.com/stefanLeong/S2CRNet

Image Completion/Inpainting - 图像修复

Learning Prior Feature and Attention Enhanced Image Inpainting

  • Paper: https://arxiv.org/abs/2208.01837
  • Code: https://github.com/ewrfcas/MAE-FAR

Perceptual Artifacts Localization for Inpainting

  • Paper: https://arxiv.org/abs/2208.03357
  • Code: https://github.com/owenzlz/PAL4Inpaint

High-Fidelity Image Inpainting with GAN Inversion

  • Paper: https://arxiv.org/abs/2208.11850

Unbiased Multi-Modality Guidance for Image Inpainting

  • Paper: https://arxiv.org/abs/2208.11844

Image Inpainting with Cascaded Modulation GAN and Object-Aware Training

  • Paper: https://arxiv.org/abs/2203.11947
  • Code: https://github.com/htzheng/CM-GAN-Inpainting

Inpainting at Modern Camera Resolution by Guided PatchMatch with Auto-Curation

  • Paper: ECVA | European Computer Vision Association

Diverse Image Inpainting with Normalizing Flow

  • Paper: ECVA | European Computer Vision Association

Hourglass Attention Network for Image Inpainting

  • Paper: ECVA | European Computer Vision Association

Perceptual Artifacts Localization for Inpainting

  • Paper: ECVA | European Computer Vision Association

Don't Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context

  • Paper: https://arxiv.org/abs/2207.10273
  • Code: https://github.com/lcy0604/CTRNet
  • Tags: Text Removal

The Surprisingly Straightforward Scene Text Removal Method with Gated Attention and Region of Interest Generation: A Comprehensive Prominent Model Analysis

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/naver/garnet
  • Tags: Text Removal

Video Inpainting

Error Compensation Framework for Flow-Guided Video Inpainting

  • Paper: https://arxiv.org/abs/2207.10391

Flow-Guided Transformer for Video Inpainting

  • Paper: https://arxiv.org/abs/2208.06768
  • Code: https://github.com/hitachinsk/FGT

Image Colorization - 图像上色

Eliminating Gradient Conflict in Reference-based Line-art Colorization

  • Paper: https://arxiv.org/abs/2207.06095
  • Code: https://github.com/kunkun0w0/SGA

Bridging the Domain Gap towards Generalization in Automatic Colorization

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/Lhyejin/DG-Colorization

CT2: Colorization Transformer via Color Tokens

  • Paper: https://ci.idm.pku.edu.cn/Weng_ECCV22b.pdf
  • Code: https://github.com/shuchenweng/CT2

PalGAN: Image Colorization with Palette Generative Adversarial Networks

  • Paper: https://arxiv.org/abs/2210.11204
  • Code: https://github.com/shepnerd/PalGAN

BigColor: Colorization using a Generative Color Prior for Natural Images

  • Paper: https://kimgeonung.github.io/assets/bigcolor/bigcolor_main.pdf
  • Code: https://github.com/KIMGEONUNG/BigColor

Semantic-Sparse Colorization Network for Deep Exemplar-Based Colorization

  • Paper: ECVA | European Computer Vision Association

ColorFormer: Image Colorization via Color Memory Assisted Hybrid-Attention Transformer

  • Paper: ECVA | European Computer Vision Association

L-CoDer: Language-Based Colorization with Color-Object Decoupling Transformer

  • Paper: ECVA | European Computer Vision Association

Colorization for In Situ Marine Plankton Images

  • Paper: ECVA | European Computer Vision Association

Image Matting - 图像抠图

TransMatting: Enhancing Transparent Objects Matting with Transformers

  • Paper: https://arxiv.org/abs/2208.03007
  • Code: https://github.com/AceCHQ/TransMatting

One-Trimap Video Matting

  • Paper: https://arxiv.org/abs/2207.13353
  • Code: https://github.com/Hongje/OTVM

Shadow Removal - 阴影消除

Style-Guided Shadow Removal

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/jinwan1994/SG-ShadowNet

Image Compression - 图像压缩

Optimizing Image Compression via Joint Learning with Denoising

  • Paper: https://arxiv.org/abs/2207.10869
  • Code: https://github.com/felixcheng97/DenoiseCompression

Implicit Neural Representations for Image Compression

  • Paper: https://arxiv.org/abs/2112.04267
  • Code:https://github.com/YannickStruempler/inr_based_compression

Expanded Adaptive Scaling Normalization for End to End Image Compression

  • Paper: https://arxiv.org/abs/2208.03049

Content-Oriented Learned Image Compression

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/lmijydyb/COLIC

Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression

  • Paper: ECVA | European Computer Vision Association

Content Adaptive Latents and Decoder for Neural Image Compression

  • Paper: ECVA | European Computer Vision Association

Video Compression

AlphaVC: High-Performance and Efficient Learned Video Compression

  • Paper: https://arxiv.org/abs/2207.14678

CANF-VC: Conditional Augmented Normalizing Flows for Video Compression

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/NYCU-MAPL/CANF-VC

Neural Video Compression Using GANs for Detail Synthesis and Propagation

  • Paper: ECVA | European Computer Vision Association

Image Quality Assessment - 图像质量评价

FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling

  • Paper: https://arxiv.org/abs/2207.02595
  • Code: https://github.com/TimothyHTimothy/FAST-VQA

Shift-tolerant Perceptual Similarity Metric

  • Paper: https://arxiv.org/abs/2207.13686
  • Code: GitHub - abhijay9/ShiftTolerant-LPIPS

Telepresence Video Quality Assessment

  • Paper: https://arxiv.org/abs/2207.09956

A Perceptual Quality Metric for Video Frame Interpolation

  • Paper: https://arxiv.org/abs/2210.01879
  • Code: https://github.com/hqqxyy/VFIPS

Relighting/Delighting

Deep Portrait Delighting

  • Paper: ECVA | European Computer Vision Association

Geometry-Aware Single-Image Full-Body Human Relighting

  • Paper: ECVA | European Computer Vision Association

NeRF for Outdoor Scene Relighting

  • Paper: ECVA | European Computer Vision Association

Physically-Based Editing of Indoor Scene Lighting from a Single Image

  • Paper: ECVA | European Computer Vision Association

Style Transfer - 风格迁移

CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer

  • Paper: https://arxiv.org/abs/2207.04808
  • Code: https://github.com/JarrentWu1031/CCPL

Image-Based CLIP-Guided Essence Transfer

  • Paper: https://arxiv.org/abs/2110.12427
  • Code: https://github.com/hila-chefer/TargetCLIP

Learning Graph Neural Networks for Image Style Transfer

  • Paper: https://arxiv.org/abs/2207.11681

WISE: Whitebox Image Stylization by Example-based Learning

  • Paper: https://arxiv.org/abs/2207.14606
  • Code: https://github.com/winfried-loetzsch/wise

Language-Driven Artistic Style Transfer

  • Paper: ECVA | European Computer Vision Association

MoDA: Map Style Transfer for Self-Supervised Domain Adaptation of Embodied Agents

  • Paper: ECVA | European Computer Vision Association

JoJoGAN: One Shot Face Stylization

  • Paper: https://arxiv.org/abs/2112.11641
  • Code: https://github.com/mchong6/JoJoGAN

EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer

  • Paper: https://arxiv.org/abs/2207.09840
  • Code: https://github.com/Chenyu-Yang-2000/EleGANt
  • Tags: Makeup Transfer

RamGAN: Region Attentive Morphing GAN for Region-Level Makeup Transfer

  • Paper: ECVA | European Computer Vision Association
  • Tags: Makeup Transfer

Image Editing - 图像编辑

Context-Consistent Semantic Image Editing with Style-Preserved Modulation

  • Paper: https://arxiv.org/abs/2207.06252
  • Code: https://github.com/WuyangLuo/SPMPGAN

GAN with Multivariate Disentangling for Controllable Hair Editing

  • Paper: https://raw.githubusercontent.com/XuyangGuo/xuyangguo.github.io/main/database/CtrlHair/CtrlHair.pdf
  • Code: https://github.com/XuyangGuo/CtrlHair

Paint2Pix: Interactive Painting based Progressive Image Synthesis and Editing

  • Paper: https://arxiv.org/abs/2208.08092
  • Code: https://github.com/1jsingh/paint2pix

High-fidelity GAN Inversion with Padding Space

  • Paper: https://arxiv.org/abs/2203.11105
  • Code: https://github.com/EzioBy/padinv

Text2LIVE: Text-Driven Layered Image and Video Editing

  • Paper: https://arxiv.org/abs/2204.02491
  • Code: https://github.com/omerbt/Text2LIVE

IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion

  • Paper: https://arxiv.org/abs/2209.10811

Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment

  • Paper: https://arxiv.org/abs/2208.07765
  • Code: https://github.com/Taeu/Style-Your-Hair

HairNet: Hairstyle Transfer with Pose Changes

  • Paper: ECVA | European Computer Vision Association

End-to-End Visual Editing with a Generatively Pre-trained Artist

  • Paper: ECVA | European Computer Vision Association

The Anatomy of Video Editing: A Dataset and Benchmark Suite for AI-Assisted Video Editing

  • Paper: ECVA | European Computer Vision Association

Scraping Textures from Natural Images for Synthesis and Editing

  • Paper: ECVA | European Computer Vision Association

VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance

  • Paper: ECVA | European Computer Vision Association

Editing Out-of-Domain GAN Inversion via Differential Activations

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/HaoruiSong622/Editing-Out-of-Domain

ChunkyGAN: Real Image Inversion via Segments

  • Paper: ECVA | European Computer Vision Association

FairStyle: Debiasing StyleGAN2 with Style Channel Manipulations

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/catlab-team/fairstyle

A Style-Based GAN Encoder for High Fidelity Reconstruction of Images and Videos

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/InterDigitalInc/FeatureStyleEncoder

Rayleigh EigenDirections (REDs): Nonlinear GAN latent space traversals for multidimensional features

  • Paper: ECVA | European Computer Vision Association

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

Text-to-Image / Text Guided / Multi-Modal

TIPS: Text-Induced Pose Synthesis

  • Paper: https://arxiv.org/abs/2207.11718
  • Code: https://github.com/prasunroy/tips

TISE: A Toolbox for Text-to-Image Synthesis Evaluation

  • Paper: https://arxiv.org/abs/2112.01398
  • Code: https://github.com/VinAIResearch/tise-toolbox

Learning Visual Styles from Audio-Visual Associations

  • Paper: https://arxiv.org/abs/2205.05072
  • Code: https://github.com/Tinglok/avstyle

Multimodal Conditional Image Synthesis with Product-of-Experts GANs

  • Paper: ECVA | European Computer Vision Association
  • Project: https://deepimagination.cc/PoE-GAN/

NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion

  • Paper: ECVA | European Computer Vision Association

Make-a-Scene: Scene-Based Text-to-Image Generation with Human Priors

  • Paper: ECVA | European Computer Vision Association

Trace Controlled Text to Image Generation

  • Paper: ECVA | European Computer Vision Association

Audio-Driven Stylized Gesture Generation with Flow-Based Model

  • Paper: ECVA | European Computer Vision Association

No Token Left Behind: Explainability-Aided Image Classification and Generation

  • Paper: ECVA | European Computer Vision Association

Image-to-Image / Image Guided

End-to-end Graph-constrained Vectorized Floorplan Generation with Panoptic Refinement

  • Paper: https://arxiv.org/abs/2207.13268

ManiFest: Manifold Deformation for Few-shot Image Translation

  • Paper: https://arxiv.org/abs/2111.13681
  • Code: https://github.com/cv-rits/ManiFest

VecGAN: Image-to-Image Translation with Interpretable Latent Directions

  • Paper: https://arxiv.org/abs/2207.03411

DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation

  • Paper: https://arxiv.org/abs/2207.06124
  • Code: https://github.com/Huage001/DynaST

Cross Attention Based Style Distribution for Controllable Person Image Synthesis

  • Paper: https://arxiv.org/abs/2208.00712
  • Code: GitHub - xyzhouo/CASD

Vector Quantized Image-to-Image Translation

  • Paper: https://arxiv.org/abs/2207.13286
  • Code: https://github.com/cyj407/VQ-I2I

URUST: Ultra-high-resolution unpaired stain transformation via Kernelized Instance Normalization

  • Paper: https://arxiv.org/abs/2208.10730
  • Code: https://github.com/Kaminyou/URUST

General Object Pose Transformation Network from Unpaired Data

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/suyukun666/UFO-PT

Unpaired Image Translation via Vector Symbolic Architectures

  • Paper: https://arxiv.org/abs/2209.02686
  • Code: https://github.com/facebookresearch/vsait

Supervised Attribute Information Removal and Reconstruction for Image Manipulation

  • Paper: https://arxiv.org/abs/2207.06555
  • Code: https://github.com/NannanLi999/AIRR

Bi-Level Feature Alignment for Versatile Image Translation and Manipulation

  • Paper: ECVA | European Computer Vision Association

Multi-Curve Translator for High-Resolution Photorealistic Image Translation

  • Paper: ECVA | European Computer Vision Association

CoGS: Controllable Generation and Search from Sketch and Style

  • Paper: ECVA | European Computer Vision Association

AgeTransGAN for Facial Age Transformation with Rectified Performance Metrics

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/AvLab-CV/AgeTransGAN

Others for image generation

StyleLight: HDR Panorama Generation for Lighting Estimation and Editing

  • Paper: https://arxiv.org/abs/2207.14811
  • Code: https://github.com/Wanggcong/StyleLight

Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling

  • Paper: https://arxiv.org/abs/2207.02196
  • Code: https://github.com/fudan-zvg/PDS

GAN Cocktail: mixing GANs without dataset access

  • Paper: https://arxiv.org/abs/2106.03847
  • Code: https://github.com/omriav/GAN-cocktail

Compositional Visual Generation with Composable Diffusion Models

  • Paper: https://arxiv.org/abs/2206.01714
  • Code: https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch

Adaptive-Feature-Interpolation-for-Low-Shot-Image-Generation

  • Paper: https://arxiv.org/abs/2112.02450
  • Code: https://github.com/dzld00/Adaptive-Feature-Interpolation-for-Low-Shot-Image-Generation

StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pretrained StyleGAN

  • Paper: https://arxiv.org/abs/2203.04036
  • Code: https://github.com/FeiiYin/StyleHEAT

WaveGAN: An Frequency-aware GAN for High-Fidelity Few-shot Image Generation

  • Paper: https://arxiv.org/abs/2207.07288
  • Code: https://github.com/kobeshegu/ECCV2022_WaveGAN

FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANs

  • Paper: https://arxiv.org/abs/2207.08630
  • Code: https://github.com/iceli1007/FakeCLR

Auto-regressive Image Synthesis with Integrated Quantization

  • Paper: https://arxiv.org/abs/2207.10776
  • Code: https://github.com/fnzhan/IQ-VAE

PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation

  • Paper: https://arxiv.org/abs/2204.00833
  • Code: https://github.com/BlingHe/PixelFolder

DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta

  • Paper: https://arxiv.org/abs/2207.10271
  • Code: https://github.com/bcmi/DeltaGAN-Few-Shot-Image-Generation

Generator Knows What Discriminator Should Learn in Unconditional GANs

  • Paper: https://arxiv.org/abs/2207.13320
  • Code: https://github.com/naver-ai/GGDR

Hierarchical Semantic Regularization of Latent Spaces in StyleGANs

  • Paper: https://arxiv.org/abs/2208.03764
  • Code: https://drive.google.com/file/d/1gzHTYTgGBUlDWyN_Z3ORofisQrHChg_n/view

FurryGAN: High Quality Foreground-aware Image Synthesis

  • Paper: https://arxiv.org/abs/2208.10422
  • Project: FurryGAN

Improving GANs for Long-Tailed Data through Group Spectral Regularization

  • Paper: https://arxiv.org/abs/2208.09932
  • Code: https://drive.google.com/file/d/1aG48i04Q8mOmD968PAgwEvPsw1zcS4Gk/view

Exploring Gradient-based Multi-directional Controls in GANs

  • Paper: https://arxiv.org/abs/2209.00698
  • Code: https://github.com/zikuncshelly/GradCtrl

Improved Masked Image Generation with Token-Critic

  • Paper: https://arxiv.org/abs/2209.04439

Weakly-Supervised Stitching Network for Real-World Panoramic Image Generation

  • Paper: https://arxiv.org/abs/2209.05968
  • Project: Weakly-Supervised Stitching Network for Real-World Panoramic Image Generation

Any-Resolution Training for High-Resolution Image Synthesis

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/chail/anyres-gan

BIPS: Bi-modal Indoor Panorama Synthesis via Residual Depth-Aided Adversarial Learning

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/chang9711/BIPS

Few-Shot Image Generation with Mixup-Based Distance Learning

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/reyllama/mixdl

StyleGAN-Human: A Data-Centric Odyssey of Human Generation

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/stylegan-human/StyleGAN-Human

StyleFace: Towards Identity-Disentangled Face Generation on Megapixels

  • Paper: ECVA | European Computer Vision Association

Contrastive Learning for Diverse Disentangled Foreground Generation

  • Paper: ECVA | European Computer Vision Association

BLT: Bidirectional Layout Transformer for Controllable Layout Generation

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/google-research/google-research/tree/master/layout-blt

Entropy-Driven Sampling and Training Scheme for Conditional Diffusion Generation

  • Paper: https://arxiv.org/abs/2206.11474
  • Code: https://github.com/ZGCTroy/ED-DPM

Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes

  • Paper: ECVA | European Computer Vision Association

DuelGAN: A Duel between Two Discriminators Stabilizes the GAN Training

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/UCSC-REAL/DuelGAN

Video Generation

Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer

  • Paper: https://arxiv.org/abs/2204.03638
  • Code: https://github.com/SongweiGe/TATS

Controllable Video Generation through Global and Local Motion Dynamics

  • Paper: https://arxiv.org/abs/2204.06558
  • Code: GitHub - Araachie/glass: Controllable Video Generation through Global and Local Motion Dynamics. In ECCV, 2022

Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesis

  • Paper: https://arxiv.org/abs/2207.05049
  • Code: https://github.com/fast-vid2vid/fast-vid2vid

Synthesizing Light Field Video from Monocular Video

  • Paper: https://arxiv.org/abs/2207.10357
  • Code: https://github.com/ShrisudhanG/Synthesizing-Light-Field-Video-from-Monocular-Video

StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation

  • Paper: https://arxiv.org/abs/2209.06192
  • Code: https://github.com/adymaharana/storydalle

Motion Transformer for Unsupervised Image Animation

  • Paper:
  • Code: https://github.com/JialeTao/MoTrans

Sound-Guided Semantic Video Generation

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/anonymous5584/sound-guided-semantic-video-generation

Layered Controllable Video Generation

  • Paper: https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4847_ECCV_2022_paper.php

Diverse Generation from a Single Video Made Possible

  • Paper: https://arxiv.org/abs/2109.08591
  • Code: https://github.com/nivha/single_video_generation

Semantic-Aware Implicit Neural Audio-Driven Video Portrait Generation

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/alvinliu0/SSP-NeRF

EAGAN: Efficient Two-Stage Evolutionary Architecture Search for GANs

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/marsggbo/EAGAN

BlobGAN: Spatially Disentangled Scene Representations

  • Paper: https://arxiv.org/abs/2205.02837
  • Code: https://github.com/dave-epstein/blobgan

Others

Learning Local Implicit Fourier Representation for Image Warping

  • Paper: https://ipl.dgist.ac.kr/LTEW.pdf
  • Code: https://github.com/jaewon-lee-b/ltew
  • Tags: Image Warping

Dress Code: High-Resolution Multi-Category Virtual Try-On

  • Paper: https://arxiv.org/abs/2204.08532
  • Code: https://github.com/aimagelab/dress-code
  • Tags: Virtual Try-On

High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions

  • Paper: https://arxiv.org/abs/2206.14180
  • Code: https://github.com/sangyun884/HR-VITON
  • Tags: Virtual Try-On

Single Stage Virtual Try-on via Deformable Attention Flows

  • Paper: https://arxiv.org/abs/2207.09161
  • Tags: Virtual Try-On

Outpainting by Queries

  • Paper: https://arxiv.org/abs/2207.05312
  • Code: https://github.com/Kaiseem/QueryOTR
  • Tags: Outpainting

Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal

  • Paper: https://arxiv.org/abs/2207.08178
  • Code: https://github.com/thinwayliu/Watermark-Vaccine
  • Tags: Watermark Protection

Efficient Meta-Tuning for Content-aware Neural Video Delivery

  • Paper: https://arxiv.org/abs/2207.09691
  • Code: https://github.com/Neural-video-delivery/EMT-Pytorch-ECCV2022
  • Tags: Video Delivery

Human-centric Image Cropping with Partition-aware and Content-preserving Features

  • Paper: https://arxiv.org/abs/2207.10269
  • Code: https://github.com/bcmi/Human-Centric-Image-Cropping

CelebV-HQ: A Large-Scale Video Facial Attributes Dataset

  • Paper: https://arxiv.org/abs/2207.12393
  • Code: https://github.com/CelebV-HQ/CelebV-HQ
  • Tags: Dataset

Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis

  • Paper: https://arxiv.org/abs/2207.11770
  • Code: https://github.com/sstzal/DFRF
  • Tags: Talking Head Synthesis

Responsive Listening Head Generation: A Benchmark Dataset and Baseline

  • Paper: https://arxiv.org/abs/2112.13548
  • Code: https://github.com/dc3ea9f/vico_challenge_baseline

Contrastive Monotonic Pixel-Level Modulation

  • Paper: https://arxiv.org/abs/2207.11517
  • Code: https://github.com/lukun199/MonoPix

AutoTransition: Learning to Recommend Video Transition Effects

  • Paper: https://arxiv.org/abs/2207.13479
  • Code: https://github.com/acherstyx/AutoTransition

Bringing Rolling Shutter Images Alive with Dual Reversed Distortion

  • Paper: https://arxiv.org/abs/2203.06451
  • Code: https://github.com/zzh-tech/Dual-Reversed-RS

Learning Object Placement via Dual-path Graph Completion

  • Paper: https://arxiv.org/abs/2207.11464
  • Code: https://github.com/bcmi/GracoNet-Object-Placement

DeepMCBM: A Deep Moving-camera Background Model

  • Paper: https://arxiv.org/abs/2209.07923
  • Code: https://github.com/BGU-CS-VIL/DeepMCBM

Mind the Gap in Distilling StyleGANs

  • Paper: https://arxiv.org/abs/2208.08840
  • Code: https://github.com/xuguodong03/StyleKD

StyleSwap: Style-Based Generator Empowers Robust Face Swapping

  • Paper: https://arxiv.org/abs/2209.13514
  • Code: https://github.com/Seanseattle/StyleSwap
  • Tags: Face Swapping

Geometric Representation Learning for Document Image Rectification

  • Paper: ECVA | European Computer Vision Association
  • Code: https://github.com/fh2019ustc/DocGeoNet
  • Tags: Document Image Rectification

Studying Bias in GANs through the Lens of Race

  • Paper: ECVA | European Computer Vision Association
  • Tags: Racial Bias

On the Robustness of Quality Measures for GANs

  • Paper: https://arxiv.org/abs/2201.13019
  • Code: https://github.com/MotasemAlfarra/R-FID-Robustness-of-Quality-Measures-for-GANs

TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN Evaluation

  • Paper: ECVA | European Computer Vision Association
  • Tags: GAN Evaluation

AAAI2022-Low-Level-Vision

Image Restoration - 图像恢复

Unsupervised Underwater Image Restoration: From a Homology Perspective

  • Paper: AAAI2022: Unsupervised Underwater Image Restoration: From a Homology Perspective
  • Tags: Underwater Image Restoration

Panini-Net: GAN Prior based Degradation-Aware Feature Interpolation for Face Restoration

  • Paper: AAAI2022: Panini-Net: GAN Prior Based Degradation-Aware Feature Interpolation for Face Restoration
  • Code: GitHub - wyhuai/Panini-Net: [AAAI 2022] Panini-Net: GAN Prior based Degradation-Aware Feature Interpolation for Face Restoration
  • Tags: Face Restoration

Burst Restoration

Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers

  • Paper: AAAI2022: SiamTrans: Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers
  • Code: https://github.com/laulampaul/siamtrans

Video Restoration

Transcoded Video Restoration by Temporal Spatial Auxiliary Network

  • Paper: AAAI2022: Transcoded Video Restoration by Temporal Spatial Auxiliary Network
  • Tags: Transcoded Video Restoration

Super Resolution - 超分辨率

Image Super Resolution

SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution

  • Paper: AAAI2022: SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution

Efficient Non-Local Contrastive Attention for Image Super-Resolution

  • Paper: https://arxiv.org/abs/2201.03794
  • Code: GitHub - Zj-BinXia/ENLCA: This project is official implementation of 'Efficient Non-Local Contrastive Attention for Image Super-Resolution', AAAI2022

Best-Buddy GANs for Highly Detailed Image Super-Resolution

  • Paper: AAAI2022: Best-Buddy GANs for Highly Detailed Image Super-Resolution
  • Tags: GAN

Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution

  • Paper: AAAI2022: Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution
  • Tags: Text SR

Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-Based Super-Resolution

  • Paper: AAAI2022: Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-Based Super-Resolution
  • Code: GitHub - Zj-BinXia/AMSA: This project is the official implementation of 'Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-Resolution', AAAI2022
  • Tags: Reference-Based SR

Detail-Preserving Transformer for Light Field Image Super-Resolution

  • Paper: AAAI2022: Detail-Preserving Transformer for Light Field Image Super-Resolution
  • Tags: Light Field

Denoising - 去噪

Image Denoising

Generative Adaptive Convolutions for Real-World Noisy Image Denoising

  • Paper: AAAI2022: Generative Adaptive Convolutions for Real-World Noisy Image Denoising

Video Denoising

ReMoNet: Recurrent Multi-Output Network for Efficient Video Denoising

  • Paper: AAAI2022: ReMoNet: Recurrent Multi-Output Network for Efficient Video Denoising

Deblurring - 去模糊

Video Deblurring

Deep Recurrent Neural Network with Multi-Scale Bi-Directional Propagation for Video Deblurring

  • Paper: AAAI2022: Deep Recurrent Neural Network with Multi-Scale Bi-Directional Propagation for Video Deblurring

Deraining - 去雨

Online-Updated High-Order Collaborative Networks for Single Image Deraining

  • Paper: AAAI2022: ReMoNet: Recurrent Multi-Output Network for Efficient Video Denoising

Close the Loop: A Unified Bottom-up and Top-down Paradigm for Joint Image Deraining and Segmentation

  • Paper: AAAI2022: Close the Loop: A Unified Bottom-up and Top-down Paradigm for Joint Image Deraining and Segmentation
  • Tags: Joint Image Deraining and Segmentation

Dehazing - 去雾

Uncertainty-Driven Dehazing Network

  • Paper: AAAI2022: Uncertainty-Driven Dehazing Network

Demosaicing - 去马赛克

Deep Spatial Adaptive Network for Real Image Demosaicing

  • Paper: AAAI2022: Deep Spatial Adaptive Network for Real Image Demosaicing

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework Using Self-Supervised Multi-Task Learning

  • Paper: https://arxiv.org/abs/2112.01030
  • Code: https://github.com/miccaiif/TransMEF

Image Enhancement - 图像增强

Low-Light Image Enhancement

Low-Light Image Enhancement with Normalizing Flow

  • Paper: https://arxiv.org/abs/2109.05923
  • Code: https://github.com/wyf0912/LLFlow

Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement

  • Paper: AAAI2022: Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement

Semantically Contrastive Learning for Low-Light Image Enhancement

  • Paper: AAAI2022: Semantically Contrastive Learning for Low-Light Image Enhancement
  • Tags: contrastive learning

Image Matting - 图像抠图

MODNet: Trimap-Free Portrait Matting in Real Time

  • Paper: https://arxiv.org/abs/2011.11961
  • Code: https://github.com/ZHKKKe/MODNet

Shadow Removal - 阴影消除

Efficient Model-Driven Network for Shadow Removal

  • Paper: AAAI2022: Efficient Model-Driven Network for Shadow Removal

Image Compression - 图像压缩

Towards End-to-End Image Compression and Analysis with Transformers

  • Paper: https://arxiv.org/abs/2112.09300
  • Code: https://github.com/BYchao100/Towards-Image-Compression-and-Analysis-with-Transformers
  • Tags: Transformer

OoDHDR-Codec: Out-of-Distribution Generalization for HDR Image Compression

  • Paper: AAAI2022: OoDHDR-Codec: Out-of-Distribution Generalization for HDR Image Compression

Two-Stage Octave Residual Network for End-to-End Image Compression

  • Paper: AAAI2022: Two-Stage Octave Residual Network for End-to-End Image Compression

Image Quality Assessment - 图像质量评价

Content-Variant Reference Image Quality Assessment via Knowledge Distillation

  • Paper: AAAI2022: Content-Variant Reference Image Quality Assessment via Knowledge Distillation

Perceptual Quality Assessment of Omnidirectional Images

  • Paper: AAAI2022: Perceptual Quality Assessment of Omnidirectional Images
  • Tags: Omnidirectional Images

Style Transfer - 风格迁移

Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization

  • Paper: https://arxiv.org/abs/2103.11784
  • Code: GitHub - czczup/URST: [AAAI 2022] Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization

Deep Translation Prior: Test-Time Training for Photorealistic Style Transfer

  • Paper: AAAI2022: Deep Translation Prior: Test-Time Training for Photorealistic Style Transfer

Image Editing - 图像编辑

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal

  • Paper: AAAI2022: SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal
  • Code: https://github.com/Snowfallingplum/SSAT
  • Tags: Makeup Transfer and Removal

Assessing a Single Image in Reference-Guided Image Synthesis

  • Paper: AAAI2022: Assessing a Single Image in Reference-Guided Image Synthesis

Interactive Image Generation with Natural-Language Feedback

  • Paper: AAAI2022: Interactive Image Generation with Natural-Language Feedback

PetsGAN: Rethinking Priors for Single Image Generation

  • Paper: AAAI2022: PetsGAN: Rethinking Priors for Single Image Generation

Pose Guided Image Generation from Misaligned Sources via Residual Flow Based Correction

  • Paper: AAAI2022: Pose Guided Image Generation from Misaligned Sources via Residual Flow Based Correction

Hierarchical Image Generation via Transformer-Based Sequential Patch Selection

  • Paper: AAAI2022: Hierarchical Image Generation via Transformer-Based Sequential Patch Selection

Style-Guided and Disentangled Representation for Robust Image-to-Image Translation

  • Paper: AAAI2022: Style-Guided and Disentangled Representation for Robust Image-to-Image Translation

OA-FSUI2IT: A Novel Few-Shot Cross Domain Object Detection Framework with Object-Aware Few-shot Unsupervised Image-to-Image Translation

  • Paper: AAAI2022: OA-FSUI2IT: A Novel Few-Shot Cross Domain Object Detection Framework with Object-Aware Few-shot Unsupervised Image-to-Image Translation
  • Code: https://github.com/emdata-ailab/FSCD-Det
  • Tags: Image-to-Image Translation used for Object Detection

Video Generation

Learning Temporally and Semantically Consistent Unpaired Video-to-Video Translation through Pseudo-Supervision from Synthetic Optical Flow

  • Paper: AAAI2022: Learning Temporally and Semantically Consistent Unpaired Video-to-Video Translation through Pseudo-Supervision from Synthetic Optical Flow
  • Code: GitHub - wangkaihong/Unsup_Recycle_GAN: Code for "Learning Temporally and Semantically Consistent Unpaired Video-to-video Translation Through Pseudo-Supervision From Synthetic Optical Flow", AAAI 2022

参考

什么是low-level、high-level任务_low-level任务_WTHunt的博客-CSDN博客

在 CV 领域里 low-level vision 前景怎么样? - 知乎 (zhihu.com)

GitHub - DarrenPan/Awesome-CVPR2023-Low-Level-Vision: A Collection of Papers and Codes in CVPR2023/2022 about low level vision文章来源地址https://www.toymoban.com/news/detail-473330.html

  • Awesome-CVPR2022-Low-Level-Vision
  • Awesome-ECCV2022-Low-Level-Vision
  • Awesome-AAAI2022-Low-Level-Vision
  • Awesome-NeurIPS2021-Low-Level-Vision
  • Awesome-ICCV2021-Low-Level-Vision
  • Awesome-CVPR2021/CVPR2020-Low-Level-Vision
  • Awesome-ECCV2020-Low-Level-Vision

到了这里,关于【论文合集】Awesome Low Level Vision的文章就介绍完了。如果您还想了解更多内容,请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章,希望大家以后多多支持TOY模板网!

本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如若转载,请注明出处: 如若内容造成侵权/违法违规/事实不符,请点击违法举报进行投诉反馈,一经查实,立即删除!

领支付宝红包 赞助服务器费用

相关文章

  • 【论文笔记】BiFormer: Vision Transformer with Bi-Level Routing Attention

    论文地址:BiFormer: Vision Transformer with Bi-Level Routing Attention 代码地址:https://github.com/rayleizhu/BiFormer vision transformer中Attention是极其重要的模块,但是它有着非常大的缺点:计算量太大。 BiFormer提出了Bi-Level Routing Attention,在Attention计算时,只关注最重要的token,由此来降低计算量

    2024年01月25日
    浏览(88)
  • 【论文合集】Awesome Anomaly Detection

    github:GitHub - bitzhangcy/Deep-Learning-Based-Anomaly-Detection Anomaly Detection : The process of detectingdata instances that  significantly deviate  from the majority of the whole dataset. Contributed by Chunyang Zhang. 目录 Survey Papers Methodology AutoEncoder GAN Flow Diffusion Model Transformer Representation Learning Nonparametric Approach Rei

    2024年02月08日
    浏览(47)
  • 【论文合集】Awesome Transfer Learning

    目录 Papers (论文) 1.Introduction and Tutorials (简介与教程) 2.Transfer Learning Areas and Papers (研究领域与相关论文) 3.Theory and Survey (理论与综述) 4.Code (代码) 5.Transfer Learning Scholars (著名学者) 6.Transfer Learning Thesis (硕博士论文) 7.Datasets and Benchmarks (数据集与评测结果) 8.Transfer Learning Challen

    2024年02月06日
    浏览(84)
  • 基于yolov5的PCB缺陷检测,引入CVPR 2023 BiFormer:Vision Transformer with Bi-Level Routing Attention提升检测精度

    目录 1.PCB数据集介绍 1.1 通过split_train_val.py得到trainval.txt、val.txt、test.txt  1.2 通过voc_label.py得到适合yolov5训练需要的 2.基于Yolov5 的PCB缺陷识别 2.1配置 pcb.yaml  2.2 修改yolov5s_pcb.yaml 2.3 超参数修改train.py 3.实验结果分析 3.1  CVPR 2023 BiFormer: 基于动态稀疏注意力构建高效金字塔

    2024年02月06日
    浏览(48)
  • 【论文合集】Awesome Object Detection in Aerial Images

    No. Year Pub. Title Links 08 2022 arXiv Towards Large-Scale Small Object Detection: Survey and Benchmarks Gong Cheng, Xiang Yuan, Xiwen Yao, Kebing Yan, Qinghua Zeng, Junwei Han Paper/Data 07 2021 PAMI Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges  DOTA     Jian Ding, Nan Xue, Gui-Song Xia, Xiang Bai, et al. Paper/Proj 06 20

    2024年02月05日
    浏览(54)
  • RLE 稀疏水平集 RLE sparse level sets 论文阅读笔记

    原文: Houston, Ben, Mark Wiebe, and Chris Batty. “RLE sparse level sets.” ACM SIGGRAPH 2004 Sketches. 2004. 137. 只有一页,这就是技术草案的含金量吗 run-length encoded, RLE 游程编码 为什么 run-length 会被翻译为游程 我理解它把连续的重复出现的数字编码成 值+出现次数 的思想 但是还是理解不了这

    2024年02月22日
    浏览(46)
  • 弱监督实例分割 Box-supervised Instance Segmentation with Level Set Evolution 论文笔记

    写在前面   这是一篇基于 Box 的弱监督实例分割文章,之前也分享过几篇(主页有,欢迎关注一下呗~),采用旧纸堆里面翻出来的能量函数来做弱监督。 论文地址:Box-supervised Instance Segmentation with Level Set Evolution 代码地址:https://github.com/LiWentomng/boxlevelset 收录于:ECCV 202

    2023年04月18日
    浏览(50)
  • Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes 论文笔记&环境配置

    发布于 CVPR 2021 论文介绍了一种具有神经SDF的复杂几何实时渲染方法。 论文提出了一种神经SDF表示,可以有效地捕获多个LOD,并以最先进的质量重建3D几何图形。 论文中的架构可以以比传统方法具有更高视觉保真度的压缩格式表示 3D 形状,并且即使在单个学习示例中也能跨不

    2024年01月24日
    浏览(45)
  • sqli 靶场 Level23-Level30 wp

    level-23 (注释被过滤) 抓包 略 寻找注入点 ● id=1’,id=1’\\\',成周期性变化 POC ● POC: id=1’+and+extractValue(1,concat(0x7e,user()))–+’ 结果:failed。怀疑–被过滤掉了,试试前后闭合方案 ● POC: id=1’+and+extractValue(1,concat(0x7e,user()))+and+’ 结果:ok。 level-24(二次注入) 这一关比较特殊

    2024年02月06日
    浏览(41)
  • Unity VR:Oculus Integration 中 OVRManager 的 Eye Level,Floor Level,Stage 的区别

    此教程相关的详细教案,文档,思维导图和工程文件会放入 Spatial XR 社区 。这是一个高质量知识星球 XR 社区,博主目前在内担任 XR 开发的讲师。此外,该社区提供教程答疑、及时交流、进阶教程、外包、行业动态等服务。 社区链接: Spatial XR 高级社区(知识星球) Spatial

    2024年02月13日
    浏览(46)

觉得文章有用就打赏一下文章作者

支付宝扫一扫打赏

博客赞助

微信扫一扫打赏

请作者喝杯咖啡吧~博客赞助

支付宝扫一扫领取红包,优惠每天领

二维码1

领取红包

二维码2

领红包