yangxy/gpen

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Blind Face Restoration in the Wild
20.2K runs

Run time and cost

Predictions run on Nvidia T4 GPU hardware. Predictions typically complete within 59 seconds. The predict time for this model varies significantly based on the inputs.

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GAN Prior Embedded Network for Blind Face Restoration in the Wild

Paper | Supplementary | Demo

Tao Yang, Peiran Ren, Xuansong Xie, Lei Zhang
DAMO Academy, Alibaba Group, Hangzhou, China
Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

Main idea

Citation

If our work is useful for your research, please consider citing:

@inproceedings{Yang2021GPEN,
    title={GAN Prior Embedded Network for Blind Face Restoration in the Wild},
    author={Tao Yang, Peiran Ren, Xuansong Xie, and Lei Zhang},
    booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2021}
}

License

© Alibaba, 2021. For academic and non-commercial use only.

Acknowledgments

We borrow some codes from Pytorch_Retinaface and stylegan2-pytorch.

Contact

If you have any questions or suggestions about this paper, feel free to reach me at yangtao9009@gmail.com.

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