Bringing Old Films Back to Life

Lagent_003_concat.mp4

Project Page | Paper (ArXiv) | Supplemental Material

This repository is the official pytorch implementation of our CVPR 2022 paper, Bringing Old Films Back to Life.

Ziyu Wan¹, Bo Zhang², Dongdong Chen³, Jing Liao¹
¹City University of Hong Kong, ²Microsoft Research, ³Microsoft Cloud AI

🌟 Pipeline

⏳ To Do

Release training code
Release testing code
Release pre-trained models
Add Google Colab

📔 Citation

If you find our work useful for your research, please consider citing the following papers :)

@article{wan2022oldfilm,
  title={Bringing Old Films Back to Life},
  author={Wan, Ziyu and Zhang, Bo and Chen, Dongdong and Liao, Jing},
  journal={CVPR},
  year={2022}
}

Want to restore the old photos as well? Try and cite our old photo restoration algorithm here.

@inproceedings{wan2020bringing,
title={Bringing Old Photos Back to Life},
author={Wan, Ziyu and Zhang, Bo and Chen, Dongdong and Zhang, Pan and Chen, Dong and Liao, Jing and Wen, Fang},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={2747--2757},
year={2020}
}

Powerful Image Completion Transformer (ICT), which could effectively recover the masked regions.

@article{wan2021high,
  title={High-Fidelity Pluralistic Image Completion with Transformers},
  author={Wan, Ziyu and Zhang, Jingbo and Chen, Dongdong and Liao, Jing},
  journal={arXiv preprint arXiv:2103.14031},
  year={2021}
}

💡 Acknowledgments

We would like to thank anonymous reviewers for their constructive comments.

📨 Contact

This repo is currently maintained by Ziyu Wan (@Raywzy) and is for academic research use only. Discussions and questions are welcome via raywzy@gmail.com.