[ECCV 2026] PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation

Model Description

Here are two models based on Wan2.1-1.3B and Wan2.1-14B for physically consistent text-to-video generation. The two models are post-trained by our re-implemented PhyGDPO algorithm on public datasets.

Github Code Link

This dataset is intended to be used together with our code. Please refer to the GitHub repository below for more detailed instructions.

https://github.com/caiyuanhao1998/Open-PhyGDPO

Huggingface Dataset Link

We also release three models based on Wan2.1-1.3B and Wan2.1-14B in the following link:

https://huggingface.co/datasets/CaiYuanhao/PhyGDPO

Project Page Link

For more video customization results, please refer to our project page:

https://caiyuanhao1998.github.io/project/PhyGDPO/

Arxiv Paper Link

For more technical details, please refer to our ECCV 2026 paper:

https://arxiv.org/abs/2512.24551

知乎中文解读

https://zhuanlan.zhihu.com/p/2060200098131350370

Citation

If you find our code, data, and models useful, please consider citing our paper:

  @inproceedings{phygdpo,
  title={PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation},
  author={Cai, Yuanhao and Li, Kunpeng and Jia, Menglin and Wang, Jialiang and Sun, Junzhe and Liang, Feng and Chen, Weifeng and Juefei-Xu, Felix and Wang, Chu and Thabet, Ali and Dai, Xiaoliang and Ju, Xuan and Yuille, Alan and Hou, Ji},
  booktitle={ECCV},
  year={2026}
}