/CooGAN

The official tensorflow implementation of "CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing" (Accepted in ECCV2020)

Primary LanguagePythonMIT LicenseMIT

CooGAN

The official tensorflow implementation of "CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing" (Accepted in ECCV2020)

Our paper can be downloaded from [arXiv]

Under construction

Dependencies

  • tensorflow-gpu <=1.3
  • pyyaml
  • paramiko
  • pillow
  • imageio
  • scipy

To cite our paper

@inproceedings{DBLP:conf/eccv/ChenNLLJTT20,
  author    = {Xuanhong Chen and
               Bingbing Ni and
               Naiyuan Liu and
               Ziang Liu and
               Yiliu Jiang and
               Loc Truong and
               Qi Tian},
  title     = {CooGAN: {A} Memory-Efficient Framework for High-Resolution Facial
               Attribute Editing},
  booktitle = {Computer Vision - {ECCV} 2020},
  year      = {2020}
}