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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ ---
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+ # TDM: Learning Few-Step Diffusion Models by Trajectory Distribution Matching
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+ <div align="center">
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+ <a href="https://tdm-t2x.github.io/"><img src="https://img.shields.io/static/v1?label=Project%20Page&message=Github-Page&color=blue&logo=github-pages"></a> &ensp;
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+ <a href="https://arxiv.org/abs/2503.06674"><img src="https://img.shields.io/static/v1?label=Paper&message=Arxiv:TDM&color=red&logo=arxiv"></a> &ensp;
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+ </div>
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+ This is the Official Repository of "[Learning Few-Step Diffusion Models by Trajectory Distribution Matching](https://arxiv.org/abs/2503.06674)", by *Yihong Luo, Tianyang Hu, Jiacheng Sun, Yujun Cai, Jing Tang*.
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+
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+ ## User Study Time!
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+ ![user_study](assets/user_study.jpg)
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+ Which one do you think is better? Some images are generated by Pixart-α (50 NFE). Some images are generated by **TDM (4 NFE)**, distilling from Pixart-α in a data-free way with merely 500 training iterations and 2 A800 hours.
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+
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+ <details>
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+
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+ <summary style="color: #1E88E5; cursor: pointer; font-size: 1.2em;"> Click for answer</summary>
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+
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+ <p style="font-size: 1.2em; margin-top: 8px;">Answers of TDM's position (left to right): bottom, bottom, top, bottom, top.</p>
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+
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+ </details>
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+
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+ ## Fast Text-to-Video Geneartion
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+
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+ Our proposed TDM can be easily extended to text-to-video.
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+
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+ <p align="center">
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+ <img src="assets/teacher.gif" alt="Teacher" width="45%">
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+ <img src="assets/student.gif" alt="Student" width="45%">
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+ </p>
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+
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+ The video on the left was generated by CogVideoX-2B (100 NFE). In the same amount of time, **TDM (4NFE)** can generate 25 videos, as shown on the right, achieving an impressive **25 times speedup without performance degradation**. (Note: The noise in the GIF is due to compression.)
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+
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+
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+ ## 🔥TODO
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+ - Pre-trained Models will be released soon.
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+
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+ ## Contact
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+
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+ Please contact Yihong Luo ([email protected]) if you have any questions about this work.
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+
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+ ## Bibtex
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+
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+ ```
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+ @misc{luo2025tdm,
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+ title={Learning Few-Step Diffusion Models by Trajectory Distribution Matching},
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+ author={Yihong Luo and Tianyang Hu and Jiacheng Sun and Yujun Cai and Jing Tang},
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+ year={2025},
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+ eprint={2503.06674},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV},
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+ url={https://arxiv.org/abs/2503.06674},
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+ }
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+ ```