htdong/Wan-Alpha_ComfyUI

Wan-Alpha

Wan-Alpha: High-Quality Text-to-Video Generation with Alpha Channel

Qualitative results of video generation using Wan-Alpha. Our model successfully generates various scenes with accurate and clearly rendered transparency. Notably, it can synthesize diverse semi-transparent objects, glowing effects, and fine-grained details such as hair.

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🔥 News

• [2025.09.30] Released Wan-Alpha v1.0, the Wan2.1-14B-T2V–adapted weights and inference code are now open-sourced.

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🌟 Showcase

Text-to-Video Generation with Alpha Channel

Prompt	Preview Video	Alpha Video
"Medium shot. A little girl holds a bubble wand and blows out colorful bubbles that float and pop in the air. The background of this video is transparent. Realistic style."

For more results, please visit Our Website

🚀 Quick Start

Please see Github for code running details

🤝 Acknowledgements

This project is built upon the following excellent open-source projects:

• DiffSynth-Studio (training/inference framework)
• Wan2.1 (base video generation model)
• LightX2V (inference acceleration)
• WanVideo_comfy (inference acceleration)

We sincerely thank the authors and contributors of these projects.

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✏ Citation

If you find our work helpful for your research, please consider citing our paper:

@misc{dong2025wanalpha,
      title={Wan-Alpha: High-Quality Text-to-Video Generation with Alpha Channel}, 
      author={Haotian Dong and Wenjing Wang and Chen Li and Di Lin},
      year={2025},
      eprint={2509.24979},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2509.24979}, 
}

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📬 Contact Us

If you have any questions or suggestions, feel free to reach out via GitHub Issues . We look forward to your feedback!