---
license: apache-2.0
language:
- en
pipeline_tag: image-to-video
datasets:
- BestWishYsh/ConsisID-preview-Data
base_model:
- THUDM/CogVideoX-5b
- THUDM/CogVideoX1.5-5B-I2V
base_model_relation: finetune
library_name: diffusers
tags:
- IPT2V
---

<div align=center>
<img src="https://github.com/PKU-YuanGroup/ConsisID/blob/main/asserts/ConsisID_logo.png?raw=true" width="150px">
</div>

<h1 align="center"> <a href="https://pku-yuangroup.github.io/ConsisID">Identity-Preserving Text-to-Video Generation by Frequency Decomposition</a></h1>

<h5 align="center"> If you like our project, please give us a star ⭐ on GitHub for the latest update.  </h2>

## 😍 Gallery

Identity-Preserving Text-to-Video Generation.
[![Demo Video of ConsisID](https://github.com/user-attachments/assets/634248f6-1b54-4963-88d6-34fa7263750b)](https://www.youtube.com/watch?v=PhlgC-bI5SQ)
or you can click <a href="https://github.com/SHYuanBest/shyuanbest_media/raw/refs/heads/main/ConsisID/showcase_videos.mp4">here</a> to watch the video.

## Description
- **Repository:** [Code](https://github.com/PKU-YuanGroup/ConsisID), [Page](https://pku-yuangroup.github.io/ConsisID/), [Data](https://huggingface.co/datasets/BestWishYsh/ConsisID-preview-Data)
- **Paper:** arxiv.org/abs/2411.17440
- **Point of Contact:** [Shenghai Yuan](shyuan-cs@hotmail.com)

## ✏️ Citation
If you find our paper and code useful in your research, please consider giving a star and citation.

```BibTeX
@article{yuan2024identity,
  title={Identity-Preserving Text-to-Video Generation by Frequency Decomposition},
  author={Yuan, Shenghai and Huang, Jinfa and He, Xianyi and Ge, Yunyuan and Shi, Yujun and Chen, Liuhan and Luo, Jiebo and Yuan, Li},
  journal={arXiv preprint arXiv:2411.17440},
  year={2024}
}
```