生成式人工智能遇见3D：AIGC 时代文本生成三维的调查

摘要

生成式人工智能（AIGC，又称AI生成内容）在过去几年取得了显著进展，其中以文本引导内容生成最为实用，因为它实现了人类指导与AIGC之间的互动。由于文本转图像以及三维建模技术（如NeRF）的发展，文本转三维已成为一个新兴且高度活跃的研究领域。我们的工作进行了首次全面调查文本转三维，以帮助对这一方向感兴趣的读者迅速了解其快速发展情况。首先，我们介绍了三维数据表示，包括欧几里得数据和非欧几里得数据。在此基础上，我们介绍了各种基础技术，并总结了最近的研究如何结合这些基础技术实现令人满意的文本转三维。此外，我们总结了文本转三维技术在各种应用中的使用，包括头像生成、纹理生成、形状转换和场景生成。

English

Generative AI (AIGC, a.k.a. AI generated content) has made remarkable progress in the past few years, among which text-guided content generation is the most practical one since it enables the interaction between human instruction and AIGC. Due to the development in text-to-image as well 3D modeling technologies (like NeRF), text-to-3D has become a newly emerging yet highly active research field. Our work conducts the first yet comprehensive survey on text-to-3D to help readers interested in this direction quickly catch up with its fast development. First, we introduce 3D data representations, including both Euclidean data and non-Euclidean data. On top of that, we introduce various foundation technologies as well as summarize how recent works combine those foundation technologies to realize satisfactory text-to-3D. Moreover, we summarize how text-to-3D technology is used in various applications, including avatar generation, texture generation, shape transformation, and scene generation.

生成式人工智能遇见3D：AIGC 时代文本生成三维的调查

Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era

摘要

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