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ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

Introduction

@inproceedings{wang2018esrgan,
  title={Esrgan: Enhanced super-resolution generative adversarial networks},
  author={Wang, Xintao and Yu, Ke and Wu, Shixiang and Gu, Jinjin and Liu, Yihao and Dong, Chao and Qiao, Yu and Change Loy, Chen},
  booktitle={Proceedings of the European Conference on Computer Vision Workshops(ECCVW)},
  pages={0--0},
  year={2018}
}

Results and Models

Evaluated on RGB channels, scale pixels in each border are cropped before evaluation.

The metrics are PSNR / SSIM.

Method Set5 Set14 DIV2K Download
esrgan_psnr_x4c64b23g32_1x16_1000k_div2k 30.6428 / 0.8559 27.0543 / 0.7447 29.3354 / 0.8263 model | log
esrgan_x4c64b23g32_1x16_400k_div2k 28.2700 / 0.7778 24.6328 / 0.6491 26.6531 / 0.7340 model | log