From 6d6892a8d4cfc3377ff39c8d72bc37682a81e700 Mon Sep 17 00:00:00 2001 From: liyinshuo Date: Tue, 27 Apr 2021 13:49:46 +0800 Subject: [PATCH] Submit --- configs/restorers/rdn/README.md | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 configs/restorers/rdn/README.md diff --git a/configs/restorers/rdn/README.md b/configs/restorers/rdn/README.md new file mode 100644 index 0000000000..1a6861f35e --- /dev/null +++ b/configs/restorers/rdn/README.md @@ -0,0 +1,27 @@ +# Residual Dense Network for Image Super-Resolution + +## Introduction + + + +```bibtex +@inproceedings{zhang2018residual, + title={Residual dense network for image super-resolution}, + author={Zhang, Yulun and Tian, Yapeng and Kong, Yu and Zhong, Bineng and Fu, Yun}, + booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, + pages={2472--2481}, + year={2018} +} +``` + +## Results + +Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation. + +The metrics are `PSNR / SSIM`. + +| Method | Set5 | Set14 | DIV2K | Download | +| :------------------------------------------------------------------------------------: | :--------------: | :--------------: | :--------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | +| [rdn_x2c64b16_g1_1000k_div2k](/configs/restorers/rdn/rdn_x2c64b16_g1_1000k_div2k.py) | 35.9883 / 0.9385 | 31.8366 / 0.8920 | 34.9392 / 0.9380 | [model](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x2c64b16_g1_1000k_div2k_20210419-dc146009.pth?versionId=CAEQJxiBgMC774LGyBciIGU3ZGRkZWM3Y2Y0ZjQ2OTliZTc2NmM5ZWY0MDA1MDU3) \| [log](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x2c64b16_g1_1000k_div2k_20210419-dc146009.log.json?versionId=CAEQJxiBgICf04_HyBciIDFkMzBiY2Y2ZDE2ZDQ0ZWE4M2MxMjMwMzdhMzY1ZTUz) | +| [rdn_x3c64b16_g1_1000k_div2k](/configs/restorers/rdn/rdn_x3c64b16_g1_1000k_div2k.py) | 32.6051 / 0.8943 | 28.6338 / 0.8077 | 31.2153 / 0.8763 | [model](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x3c64b16_g1_1000k_div2k_20210419-b93cb6aa.pth?versionId=CAEQJxiBgMC3v9LFyBciIGExYWY0NTI0YWVkODQxZDRiYWNlYjViY2E5MzQ4OTc1) \| [log](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x3c64b16_g1_1000k_div2k_20210419-b93cb6aa.log.json?versionId=CAEQJxiBgMCtwtLFyBciIDNmNzZjNTUyYTk0MjQ2OTBiYjJiNDNjMTI0NGZhYmI4) | +| [rdn_x4c64b16_g1_1000k_div2k](/configs/restorers/rdn/rdn_x4c64b16_g1_1000k_div2k.py) | 30.4922 / 0.8548 | 26.9570 / 0.7423 | 29.1925 / 0.8233 | [model](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x4c64b16_g1_1000k_div2k_20210419-3577d44f.pth?versionId=CAEQJxiBgICwxdLFyBciIGFlMzVhNTBlOGEyNDQwMGI5OGJjOTJkMDQ1ZDJjOTM2) \| [log](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x4c64b16_g1_1000k_div2k_20210419-3577d44f.log.json?versionId=CAEQJxiBgIC9xtLFyBciIGQ5YTJhMjY0OTE1YjRiMTQ5OTc5YzQ2MjM4ZGVkZWQ1) |