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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A curated list of papers and open-source resources focused on 3D AIGC.
| Date | Stars |
|---|---|
| 2026-07-24 | 348 |
| 2026-07-25 | 348 |
| 2026-07-28 | 348 |
| 2026-07-30 | 348 |
| 2026-08-06 | 348 |
Today
— stars today
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growth rate 0.00%/day
# Awesome 3D AIGC Resources
A curated list of papers and open-source resources focused on 3D AIGC, intended to keep pace with the anticipated surge of research in the coming months. If you have any additions or suggestions, feel free to contribute. Additional resources like blog posts, videos, etc. are also welcome.
<p align="center">
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<img alt="GitHub stars" src="https://img.shields.io/github/stars/mdyao/Awesome-3D-AIGC?color=0088ff" />
<a href="https://github.com/mdyao/Awesome-3D-AIGC"><img src="https://img.shields.io/badge/Awesome-3DAIGC-orange"/></a>
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</p>
## Table of contents
- [Survey](#survey)
- [Text to 3D Generation](#text-to-3d-generation)
- [Image to 3D Generation](#image-to-3d-generation)
- [Audio to 3D Generation](#audio-to-3d-generation)
- [3D Editing](#3d-editing)
- [Human Avatar Generation](#human-avatar-generation)
- [City/Autonomous Driving](#autonomous-driving)
- [SLAM](#slam)
- [BioMedical](#biomedical)
- [4D AIGC](#4d-aigc)
- [Misc](#misc)
- [Open Source Implementations](#open-source-implementations)
* [Reference](#reference)
* [Unofficial Implementations](#unofficial-implementations)
* [Datasets](#datasets)
* [Other](#other)
- [Practical Tools](#practical-tools)
- [Blog Posts](#blog-posts)
- [Tutorial Videos](#tutorial-videos)
- [Credits](#credits)
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<summary><b>Update Log:</b></summary>
<be>
**Mar. 4, 2024**: Update several CVPR 2024 papers.
**Jan 23, 2024**: Update several ICLR 2024 papers.
**Jan 19, 2024**: Update several ICLR 2024 papers.
**Jan 11, 2024**: Add AGG and recent papers.
**Jan 10, 2024**: Add DreamGaussian (3D version) and several avatar papers.
**Jan 6, 2024**: Add recent papers.
**Jan 2, 2024**: Add papers to image to 3d generation.
**Dec 29, 2023**: Contribute to the section on text-to-3d by adding new papers with their publication years.
**Dec 27, 2023**: Initial list with first 15 papers.
</details>
<be>
<div align=center><img src="https://github.com/mdyao/Awesome-3D-AIGC/assets/33108887/2bee41c0-b19c-4047-ae26-02ca2af2c38f"/></div>
## Survey:
### 1. Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era [arxiv 2023.05]
**Authors**: Chenghao Li, Chaoning Zhang, Atish Waghwase, Lik-Hang Lee, Francois Rameau, Yang Yang, Sung-Ho Bae, Choong Seon Hong
<details span>
<summary><b>Abstract</b></summary>
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.
</details>
[📄 Paper](https://arxiv.org/pdf/2305.06131.pdf)
### 2. Deep Generative Models on 3D Representations: A Survey [arxiv 2023.10]
**Authors**: Zifan Shi, Sida Peng, Yinghao Xu, Andreas Geiger, Yiyi Liao, Yujun Shen
<details span>
<summary><b>Abstract</b></summaExcerpt of 224,636 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ac03f41e84dc54b8, topic:computer-vision, topic:nerf