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.

本研究主要介绍了生成人工智能中的文本导向内容生成，着重探讨其中的文本导向三维技术，提供了一份关于该领域的综合调查报告。该报告介绍了三维数据表示、相关技术及其在不同应用方面的应用，包括头像生成、纹理生成、形状变换和场景生成，以及使用NeRF等文本到图像与三维建模技术的新兴方向的最新进展。

生成型人工智能遇上3D：AIGC时代的文本到3D调查