README.md

---
base_model:
- Wan-AI/Wan2.1-T2V-1.3B
- Qwen/Qwen-Image-Edit-2509
language:
- en
license: apache-2.0
pipeline_tag: other
library_name: diffusers
arxiv: 2601.20175
tags:
- video
- image
- stylization
- style-transfer
---

<div align="center">

<h1><b>TeleStyle: Content-Preserving Style Transfer in Images and Videos</b></h1>

</div>

<div align="center">
Shiwen Zhang, Xiaoyan Yang, Bojia Zi, Haibin Huang, Chi Zhang, Xuelong Li
  <p>
    Institute of Artificial Intelligence, China Telecom (TeleAI)&nbsp;&nbsp;
  </p>
</div>

<p align="center">
  <a href='https://tele-ai.github.io/TeleStyle/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
  &nbsp;
  <a href="http://arxiv.org/abs/2601.20175"><img src="https://img.shields.io/static/v1?label=Arxiv&message=TeleStyle&color=red&logo=arxiv"></a>
  &nbsp;
  <a href='https://huggingface.co/Tele-AI/TeleStyle'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-orange'></a>
  &nbsp;
  <a href="https://github.com/Tele-AI/TeleStyle">
    <img src="https://img.shields.io/badge/GitHub-Code-red?logo=github">
  </a>
</p>

TeleStyle is a lightweight yet effective model for both image and video stylization. Built upon Qwen-Image-Edit, it leverages a Curriculum Continual Learning framework to achieve high-fidelity content preservation and style customization across diverse, in-the-wild style categories.

## 🔔 News

- [2026-01-28]: Released [Code](https://github.com/Tele-AI/TeleStyle), [Model](https://huggingface.co/Tele-AI/TeleStyle), [Paper](http://arxiv.org/abs/2601.20175).

## How to use

### 1. Installation

```bash
pip install -r requirements.txt
```

### 2. Inference

We provide inference scripts for running TeleStyle on demo inputs for each task:

#### Image Stylization
To generate a stylized image using a reference style image and a content image:
```bash
python telestyleimage_inference.py --image_path assets/example/0.png --style_path videos/1.png --output_path results/image.png
```

#### Video Stylization
To generate a stylized video using a stylized first frame and a content video:
```bash
python telestylevideo_inference.py --video_path assets/example/1.mp4 --style_path assets/example/1-0.png --output_path results/video.mp4
```

For more details, please refer to the [**🔗 GitHub**](https://github.com/Tele-AI/TeleStyle) repository.

## 🌟 Citation

If you find TeleStyle useful for your research and applications, please cite using this BibTeX:

```bibtex
@article{teleai2026telestyle,
    title={TeleStyle: Content-Preserving Style Transfer in Images and Videos}, 
    author={Shiwen Zhang and Xiaoyan Yang and Bojia Zi and Haibin Huang and Chi Zhang and Xuelong Li},
    journal={arXiv preprint arXiv:2601.20175},
    year={2026}
}
```