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Website source code for our ACM MM'23 paper "Hierarchical Masked 3D Diffusion Model for Video Outpainting".

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# Hierarchical Masked 3D Diffusion Model for Video Outpainting

This is the repository that contains website source code for the paper "Hierarchical Masked 3D Diffusion Model for Video Outpainting". <a href='https://arxiv.org/abs/2309.02119'><img src='https://img.shields.io/badge/arXiv-2309.02119-red'></a> <a href='https://fanfanda.github.io/M3DDM/'><img src='https://img.shields.io/badge/Project-Website-orange'></a> <a href='https://github.com/alimama-creative/M3DDM-Video-Outpainting'><img src='https://img.shields.io/badge/Github-Code-green'></a>

We have made our API public at this [link](https://chuangyi.taobao.com), and merchant users (Currently only support business users) can upload video materials for video outpainting. We have provided a [tutorial](assets/Tutorial.pdf). Due to the practical application in real scenarios, after applying the video outpainting model, we have additionally included a super-resolution model to enhance the filled results after video outpainting. This is different from the pipeline used in the paper. However, in some cases, the super-resolution model may result in a performance decline.
 
## Update

- **[2024/01/12]** :fire::fire::fire: We have released the inference code and model files on our [GitHub repository](https://github.com/alimama-creative/M3DDM-Video-Outpainting).
- **[2023/11/18]** After policy review, we are ready to open-source our model within three months!
- **[2023/10/26]** Upload the tutorial PDF.

## Citation
```bash
@inproceedings{fan2023hierarchical,
  title={Hierarchical Masked 3D Diffusion Model for Video Outpainting},
  author={Fan, Fanda and Guo, Chaoxu and Gong, Litong and Wang, Biao and Ge, Tiezheng and Jiang, Yuning and Luo, Chunjie and Zhan, Jianfeng},
  booktitle={Proceedings of the 31st ACM International Conference on Multimedia},
  pages={7890--7900},
  year={2023}
}
```

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