43 citations · 54 across the 2 of their papers we have counts for
3 papers
cs.CV2021★ 11 cited
ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
Xiangtao Kong, Hengyuan Zhao, Yu Qiao +1
We aim at accelerating super-resolution (SR) networks on large images (2K-8K). The large images are usually decomposed into small sub-images in practical usages. Based on this proc…
eess.IV2020★ 43 cited
Efficient Image Super-Resolution Using Pixel Attention
Hengyuan Zhao, Xiangtao Kong, Jingwen He +2
This work aims at designing a lightweight convolutional neural network for image super resolution (SR). With simplicity bare in mind, we construct a pretty concise and effective ne…
eess.IV2020
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Kai Zhang, Martin Danelljan, Yawei Li +75
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 in…