AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Radu Timofte
Gangshan Wu
Xiaohong Liu
Yu Qiao
Xiaotong Luo
Liang Chen
Jiangtao Zhang
Lei Zhang
Liang Chen
Jiangtao Zhang
Xiaotong Luo
Jun-Ho Choi
Jun-Hyuk Kim
Xinbo Gao
Shuai Liu
Jiangtao Zhang
Xiaotong Luo
Liang Chen
Yanyun Qu
- SupR
Abstract
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor x4 based on a set of prior examples of low and corresponding high resolution images. The goal is to devise a network that reduces one or several aspects such as runtime, parameter count, FLOPs, activations, and memory consumption while at least maintaining PSNR of MSRResNet. The track had 150 registered participants, and 25 teams submitted the final results. They gauge the state-of-the-art in efficient single image super-resolution.
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