---
license: apache-2.0
pipeline_tag: text-to-video
tags:
- video-generation
- dpo
---

# Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models

This repository contains the weights for **LocalDPO**, a novel post-training framework that constructs localized preference pairs from real videos and optimizes alignment at the spatio-temporal region level for video diffusion models.

LocalDPO addresses the efficiency and ambiguity limitations of existing DPO methods. It treats high-quality real videos as positive samples and generates corresponding negatives by locally corrupting them with random spatio-temporal masks. Experiments on Wan2.1 and CogVideoX demonstrate that LocalDPO consistently improves video fidelity and temporal coherence.

- **Paper:** [Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models](https://huggingface.co/papers/2601.04068)
- **Project Page:** [https://1170300714.github.io/LocalDPO/](https://1170300714.github.io/LocalDPO/)
- **Code:** [https://github.com/1170300714/Local-DPO](https://github.com/1170300714/Local-DPO)

## Citation

```bibtex
@article{huang2026mind,
  title={Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models},
  author={Huang, Zitong and Zhang, Kaidong and Ding, Yukang and Gao, Chao and Ding, Rui and Chen, Ying and Zuo, Wangmeng},
  journal={arXiv preprint arXiv:2601.04068},
  year={2026}
}
```