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@ -18,11 +18,13 @@ The paper is accepted to [ECCV2018 PIRM Workshop](https://pirm2018.org/).
year={2018}
}
-->
@inproceedings{wang2018esrgan,
author = {Wang, Xintao and Yu, Ke and Wu, Shixiang and Gu, Jinjin and Liu, Yihao and Dong, Chao and Loy, Chen Change and Qiao, Yu and Tang, Xiaoou},
@InProceedings{wang2018esrgan,
author = {Wang, Xintao and Yu, Ke and Wu, Shixiang and Gu, Jinjin and Liu, Yihao and Dong, Chao and Qiao, Yu and Loy, Chen Change},
title = {ESRGAN: Enhanced super-resolution generative adversarial networks},
booktitle = {European Conference on Computer Vision (ECCV) Workshops},
booktitle = {The European Conference on Computer Vision Workshops (ECCVW)},
month = {September},
year = {2018}
}
<p align="center">
<img src="figures/baboon.jpg">
@ -67,6 +69,22 @@ You can interpolate the RRDB_ESRGAN and RRDB_PSNR models with alpha in [0, 1].
<img height="400" src="figures/43074.gif">
</p>
## Perceptual-driven SR Results
You can download all the resutls from [Google Drive](https://drive.google.com/drive/folders/1iaM-c6EgT1FNoJAOKmDrK7YhEhtlKcLx?usp=sharing). (:heavy_check_mark: included; :heavy_minus_sign: not included; :o: TODO)
HR images can be downloaed from [BasicSR-Datasets](https://github.com/xinntao/BasicSR#datasets).
| Datasets |LR | [*ESRGAN*](https://arxiv.org/abs/1809.00219) | [SRGAN](https://arxiv.org/abs/1609.04802) | [EnhanceNet](http://openaccess.thecvf.com/content_ICCV_2017/papers/Sajjadi_EnhanceNet_Single_Image_ICCV_2017_paper.pdf) | [CX](https://arxiv.org/abs/1803.04626) |
|:---:|:---:|:---:|:---:|:---:|:---:|
| Set5 |:heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :o:| :o: |
| Set14 | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :o:| :o: |
| BSDS100 | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :o:| :o: |
| [PIRM](https://pirm.github.io/) <br><sup>(val, test)</sup> | :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | :o:| :o: |
| [OST300](https://arxiv.org/pdf/1804.02815.pdf) |:heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | :o:| :o: |
| urban100 | :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | :o:| :o: |
| [DIV2K](https://data.vision.ee.ethz.ch/cvl/DIV2K/) <br><sup>(val, test)</sup> | :heavy_check_mark: | :heavy_check_mark: | :heavy_minus_sign: | :o:| :o: |
## ESRGAN
We improve the [SRGAN](https://arxiv.org/abs/1609.04802) from three aspects:
1. adopt a deeper model using Residual-in-Residual Dense Block (RRDB) without batch normalization layers.