RDN (CVPR'2018)
@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}
}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 | 35.9883 / 0.9385 | 31.8366 / 0.8920 | 34.9392 / 0.9380 | model | log |
| rdn_x3c64b16_g1_1000k_div2k | 32.6051 / 0.8943 | 28.6338 / 0.8077 | 31.2153 / 0.8763 | model | log |
| rdn_x4c64b16_g1_1000k_div2k | 30.4922 / 0.8548 | 26.9570 / 0.7423 | 29.1925 / 0.8233 | model | log |