62 citations · 122 across the 4 of their papers we have counts for
5 papers
Suppressing Model Overfitting for Image Super-Resolution Networks
Ruicheng Feng, Jinjin Gu, Yu Qiao +1
Large deep networks have demonstrated competitive performance in single image super-resolution (SISR), with a huge volume of data involved. However, in real-world scenarios, due to…
Blind Super-Resolution With Iterative Kernel Correction
Jinjin Gu, Hannan Lu, Wangmeng Zuo +1
Deep learning based methods have dominated super-resolution (SR) field due to their remarkable performance in terms of effectiveness and efficiency. Most of these methods assume th…
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
Xintao Wang, Kelvin C. K. Chan, Ke Yu +2
Video restoration tasks, including super-resolution, deblurring, etc, are drawing increasing attention in the computer vision community. A challenging benchmark named REDS is relea…
Boosting Optical Character Recognition: A Super-Resolution Approach
Chao Dong, Ximei Zhu, Yubin Deng +2
Text image super-resolution is a challenging yet open research problem in the computer vision community. In particular, low-resolution images hamper the performance of typical opti…
Compression Artifacts Reduction by a Deep Convolutional Network
Chao Dong, Yubin Deng, Chen Change Loy +1
Lossy compression introduces complex compression artifacts, particularly the blocking artifacts, ringing effects and blurring. Existing algorithms either focus on removing blocking…