HAT [Paper Link]

Activating More Pixels in Image Super-Resolution Transformer

Xiangyu Chen, Xintao Wang, Jiantao Zhou and Chao Dong

BibTeX

@article{chen2022activating,
  title={Activating More Pixels in Image Super-Resolution Transformer},
  author={Chen, Xiangyu and Wang, Xintao and Zhou, Jiantao and Dong, Chao},
  journal={arXiv preprint arXiv:2205.04437},
  year={2022}
}

Environment

• PyTorch >= 1.7
• BasicSR >= 1.3.4.9

Installation

pip install -r requirements.txt
python setup.py develop

How To Test

• Refer to ./options/test for the configuration file of the model to be tested, and prepare the testing data and pretrained model.
• The pretrained models are available at Google Drive or Baidu Netdisk (access code: qyrl).
• Then run the follwing codes (taking HAT_SRx4_ImageNet-pretrain.pth as an example):

python hat/test.py -opt options/test/HAT_SRx4_ImageNet-pretrain.yml

The testing results will be saved in the ./results folder.

Results

The inference results on benchmark datasets are available at Google Drive or Baidu Netdisk (access code: 63p5).

This repo is still being updated. The training codes will be released soon.