Dear friends, Thank you for keep tracking in this implementation of FSRNet (CVPR 2018 Oral Paper)

I have been spent the whole summer as an intern in Iluvatar.ai. I have been back to school, so I have time to complete the Project.

I rewrite the Train.py and other model code completely. Now I am uploading pretrained Weights on BaiduNetDisk together with Training Set.

Based on WaveletSRNet, I altered the code by adopting FSRNet network structure.

• Python 3.6
• Pytorch 1.0 or newer (Pytorch > 0.4 should be ok)
• matplotlib
• skimage

Change the option in Train.py to set the dataset's directory. I am using CelebAHQ-MASK as the training set. The GroundTruth is generated by zllrunning/face-parsing.PyTorch(https://github.com/zllrunning/face-parsing.PyTorch) with pretrained model.

Dataset Link: https://pan.baidu.com/s/1HEECUyKI5GOSrd7NPlm-ow 密码:z2ud

ON GOING :| PYTHON AND NOTEBOOK WILL BE PROVIDED. Pretrained Weights:链接:https://pan.baidu.com/s/1ZkgABGefsMjO6XhhvlBzRA 密码:libl

If you find FSRNet useful in your research, please consider citing (* indicates equal contributions):

@inproceedings{CT-FSRNet-2018,
  title={FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors},
  author={Chen, Yu* and Tai, Ying* and Liu, Xiaoming and Shen, Chunhua and Yang, Jian },
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  year={2018}
}