IMDN

Lightweight Image Super-Resolution with Information Multi-distillation Network (ACM MM 2019) This repository contains an op-for-op Paddle reimplementation of Lightweight Image Super-Resolution with Information Multi-distillation Network. It is modified from the original source code of Pytorch implementation(https://github.com/Zheng222/IMDN)

[arXiv] ##Training DIV2K dataset is used for training

Testing

• Runing testing:

# 
python test_IMDN_X2.py --test_hr_folder Test_Datasets/Set5/ --test_lr_folder Test_Datasets/Set5_LR/x2/ --output_folder results/Set5/x2 --upscale_factor 2

Results

百度网盘提取码: 8yqj or Google drive

Citation

If you find IMDN useful in your research, please consider citing:

@inproceedings{Hui-IMDN-2019,
  title={Lightweight Image Super-Resolution with Information Multi-distillation Network},
  author={Hui, Zheng and Gao, Xinbo and Yang, Yunchu and Wang, Xiumei},
  booktitle={Proceedings of the 27th ACM International Conference on Multimedia (ACM MM)},
  pages={2024--2032},
  year={2019}
}

@inproceedings{AIM19constrainedSR,
  title={AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results},
  author={Kai Zhang and Shuhang Gu and Radu Timofte and others},
  booktitle={The IEEE International Conference on Computer Vision (ICCV) Workshops},
  year={2019}
}