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eess.IV2022
Learning Multiple Probabilistic Degradation Generators for Unsupervised Real World Image Super Resolution
Sangyun Lee, Sewoong Ahn, Kwangjin Yoon
Unsupervised real world super resolution (USR) aims to restore high-resolution (HR) images given low-resolution (LR) inputs, and its difficulty stems from the absence of paired dat…
eess.IV2021
Simple and Efficient Unpaired Real-world Super-Resolution using Image Statistics
Kwangjin Yoon
Learning super-resolution (SR) network without the paired low resolution (LR) and high resolution (HR) image is difficult because direct supervision through the corresponding HR co…
eess.IV2020★ 9 cited
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte +60
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input im…