【LLM+三维场景】3D-GPT: Procedural 3D MODELING WITH LARGE LANGUAGE MODELS-Toy模板网

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3D-GPT: Procedural 3D MODELING WITH LARGE LANGUAGE MODELS 3D-GPT：使用大型语言模型进行程序化 3D 建模

2023.10

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一句话生成3D世界，未公布代码已获141星！或引发3D建模行业革命
【LLM+三维场景】3D-GPT: Procedural 3D MODELING WITH LARGE LANGUAGE MODELS,有意思的工作,nlp,3d,gpt,语言模型

Abstract

In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable parameters and rule-based systems, emerges as a promising approach. Nonetheless, it could be a demanding endeavor, given its intricate nature necessitating a deep understanding of rules, algorithms, and parameters. To reduce workload, we introduce 3D-GPT, a framework utilizing large language models~(LLMs) for instruction-driven 3D modeling. 3D-GPT positions LLMs as proficient problem solvers, dissecting the procedural 3D modeling tasks into accessible segments and appointing the apt agent for each task. 3D-GPT integrates three core agents: the task dispatch agent, the conceptualization agent, and the modeling agent. They collaboratively achieve two objectives. First, it enhances concise initial scene descriptions, evolving them into detailed forms while dynamically adapting the text based on subsequent instructions. Second, it integrates procedural generation, extracting parameter values from enriched text to effortlessly interface with 3D software for asset creation. Our empirical investigations confirm that 3D-GPT not only interprets and executes instructions, delivering reliable results but also collaborates effectively with human designers. Furthermore, it seamlessly integrates with Blender, unlocking expanded manipulation possibilities. Our work highlights the potential of LLMs in 3D modeling, offering a basic framework for future advancements in scene generation and animation.

在追求高效的自动内容创建过程中，利用可修改参数和基于规则的系统进行程序生成是一种很有前途的方法。

然而，由于其复杂性，需要对规则、算法和参数有深入的了解，这可能是一项艰巨的工作。

为了减少工作量，我们引入了 3D-GPT 框架，该框架利用大型语言模型（LLM）进行指令驱动的 3D 建模。

3D-GPT 将大型语言模型定位为熟练的问题解决者，将程序化三维建模任务分解为可访问的片段，并为每个任务指定合适的agent。

3D-GPT 集成了三个核心agent：