/GPEN

Primary LanguageJupyter Notebook

GAN Prior Embedded Network for Blind Face Restoration in the Wild

Paper | Supplementary | Demo

Tao Yang1, Peiran Ren1, Xuansong Xie1, Lei Zhang1,2
1DAMO Academy, Alibaba Group, Hangzhou, China
2Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

Face Restoration

Face Colorization

Face Inpainting

Conditional Image Synthesis (Seg2Face)

News

(2021-07-06) The training code will be released soon. Stay tuned.

(2021-10-11) The Colab demo for GPEN is available now google colab logo.

(2021-10-22) GPEN can now work with SR methods. A SR model trained by myself is provided. Replace it with your own model if necessary.

(2021-12-01) GPEN can now work on a Windows machine without compiling cuda codes. Please check it out. Thanks to Animadversio. Alternatively, you can try GPEN-Windows. Many thanks to Cioscos.

Usage

python pytorch cuda driver gcc

  • Clone this repository:
git clone https://github.com/yangxy/GPEN.git
cd GPEN
python face_enhancement.py --model GPEN-BFR-512 --size 512 --channel_multiplier 2 --narrow 1 --use_sr --indir examples/imgs --outdir examples/outs-BFR
  • Colorize faces:
python face_colorization.py
  • Complete faces:
python face_inpainting.py
  • Synthesize faces:
python segmentation2face.py

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, stylegan2-pytorch, and Real-ESRGAN.

Contact

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