Stable Video Matting with Consistent Memory Propagation

Peiqing Yang¹  Shangchen Zhou¹  Jixin Zhao¹  Qingyi Tao²  Chen Change Loy¹

¹S-Lab, Nanyang Technological University  ²SenseTime Research, Singapore 

MatAnyone is a practical human video matting framework supporting target assignment, with stable performance in both semantics of core regions and fine-grained boundary details.

🎥 For more visual results, go checkout our project page

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📮 Update

• [2025.02] 📢 📢 📢 Code and demo will be released next week 🤗
• [2025.02] This repo is created.

🔎 Overview

🎪 Interactive Demo

📑 Citation

If you find our repo useful for your research, please consider citing our paper:

 @InProceedings{yang2025matanyone,
     title     = {{MatAnyone}: Stable Video Matting with Consistent Memory Propagation},
     author    = {Yang, Peiqing and Zhou, Shangchen and Zhao, Jixin and Tao, Qingyi and Loy, Chen Change},
     booktitle = {arXiv preprint arXiv:2501.14677},
     year      = {2025}
     }

📝 License

This project is licensed under NTU S-Lab License 1.0. Redistribution and use should follow this license.

📧 Contact

If you have any questions, please feel free to reach us at peiqingyang99@outlook.com.