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Meta-SR

Official implementation of Meta-SR: A Magnification-Arbitrary Network for Super-Resolution(CVPR2019)(PyTorch)

Paper

Our code is built on EDSR(PyTorch).

Attention

I find an error in my camera-ready, the PSNR of our Meta-RDN on scale 1.2 is 40.04 not 40.40.

Requirements

Update notes

Install and run demo

  1. download the code
git clone https://github.com/XuecaiHu/Meta-SR-Pytorch.git
cd Meta-SR-Pytorch
  1. run training demo:
python main.py --model metardn --ext sep  --save metardn --lr_decay 200 --epochs 1000 --n_GPUs 1 --batch_size 1
  1. run test demo:
python main.py --model metardn --ext sep  --save metardn --n_GPUs 1 --batch_size 1 --test_only --data_test Set5 --pre_train  ./experiment/metardn/model/model_1000.pt  --save_results --scale 1.5

Train and Test as our paper

  1. prepare dataset
  1. pre_train model for test BaiduYun fetch code: btc5
    GoogleDrive

train

cd /Meta-SR-Pytorch 
python main.py --model metardn --save metardn --ext sep --lr_decay 200 --epochs 1000 --n_GPUs 4 --batch_size 16 

test

python main.py --model metardn --save metardn --ext sep --pre_train ./experiment/metardn/model/model_1000.pt --test_only --data_test Set5  --scale 1.5 --n_GPUs 1

Citation

@article{hu2019meta,
  title={Meta-SR: A Magnification-Arbitrary Network for Super-Resolution},
  author={Hu, Xuecai and Mu, Haoyuan and Zhang, Xiangyu and Wang, Zilei  and Tan, Tieniu and Sun, Jian},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
  year={2019}
}

Contact

Xuecai Hu (xuecai.hu@cripac.ia.ac.cn or huxc@mail.ustc.edu.cn)