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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.
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.
[CVPR 2025 Highlight🔥] Identity-Preserving Text-to-Video Generation by Frequency Decomposition
| Date | Stars |
|---|---|
| 2026-07-24 | 848 |
| 2026-07-25 | 848 |
| 2026-07-28 | 848 |
| 2026-07-30 | 848 |
| 2026-08-08 | 851 |
| 2026-08-17 | 853 |
| 2026-08-23 | 854 |
| 2026-08-26 | 855 |
| 2026-08-30 | 854 |
| 2026-09-01 | 855 |
| 2026-09-02 | 856 |
| 2026-09-07 | 857 |
| 2026-09-14 | 857 |
| 2026-09-19 | 857 |
| 2026-09-20 | 857 |
Today
— stars today
This week
— stars this week
This month
+4 stars this month
Momentum
0.0
growth rate 0.00%/day
<div align=center> <img src="https://github.com/PKU-YuanGroup/ConsisID/blob/main/asserts/ConsisID_logo.png?raw=true" width="150px"> </div> <h2 align="center"> <a href="https://arxiv.org/abs/2411.17440">[CVPR 2025 Highlight] Identity-Preserving Text-to-Video Generation by Frequency Decomposition</a></h2> <h5 align="center"> If you like our project, please give us a star ⭐ on GitHub for the latest update. </h2> <h5 align="center"> [](https://huggingface.co/spaces/BestWishYsh/ConsisID-preview-Space) [](https://colab.research.google.com/github/camenduru/ConsisID-jupyter/blob/main/ConsisID_jupyter.ipynb) [](https://huggingface.co/papers/2411.17440) [](https://arxiv.org/abs/2411.17440) [](https://pku-yuangroup.github.io/ConsisID/) [](https://huggingface.co/datasets/BestWishYsh/ConsisID-preview-Data) [](https://x.com/AdinaYakup/status/1862604191631573122) [](https://x.com/camenduru/status/1861957812152078701) [](https://www.youtube.com/watch?v=PhlgC-bI5SQ) [](https://github.com/PKU-YuanGroup/ConsisID/blob/main/LICENSE) [](https://github.com/PKU-YuanGroup/ConsisID/) </h5> <div align="center"> This repository is the official implementation of ConsisID, a tuning-free DiT-based controllable IPT2V model to keep human-identity consistent in the generated video. The approach draws inspiration from previous studies on frequency analysis of vision/diffusion transformers. </div> <br> <details open><summary>💡 We also have other video generation projects that may interest you ✨. </summary><p> <!-- may --> > [**Open-Sora Plan: Open-Source Large Video Generation Model**](https://arxiv.org/abs/2412.00131) <br> > Bin Lin, Yunyang Ge and Xinhua Cheng etc. <br> [](https://github.com/PKU-YuanGroup/Open-Sora-Plan) [](https://github.com/PKU-YuanGroup/Open-Sora-Plan) [](https://arxiv.org/abs/2412.00131) <br> > > [**Helios: Real Real-Time Long Video Generation Model**](https://arxiv.org/abs/2603.04379) <br> > Shenghai Yuan, Jinfa Huang and Xianyi He etc. <br> > [](https://github.com/PKU-YuanGroup/Helios) [](https://github.com/PKU-YuanGroup/Helios) [](https://arxiv.org/abs/2603.04379) <br> > > [**OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation**](https://arxiv.org/abs/2505.20292) <br> > Shenghai Yuan, Xianyi He and Yufan Deng etc. <br> > [](https://github.com/PKU-YuanGroup/OpenS2V-Nexus) [](https://github.com/PKU-YuanGroup/OpenS2V-Nexus) [](https://arxiv.org/abs/2505.202
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Shenghai Yuan · PKU-YuanGroup · China
183
Jinfa Huang · UR & PKU & UESTC
2
2
Ikko Eltociear Ashimine · Japan
1
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6e5abb9f9d1663a3, topic:video-generation, topic:text-to-video, desc:video generation