85 citations · 679 across the 51 of their papers we have counts for
11 papers · 2 filters
Reflash Dropout in Image Super-Resolution
Xiangtao Kong, Xina Liu, Jinjin Gu +2
Dropout is designed to relieve the overfitting problem in high-level vision tasks but is rarely applied in low-level vision tasks, like image super-resolution (SR). As a classic re…
Semantic-Sparse Colorization Network for Deep Exemplar-based Colorization
Yunpeng Bai, Chao Dong, Zenghao Chai +3
Exemplar-based colorization approaches rely on reference image to provide plausible colors for target gray-scale image. The key and difficulty of exemplar-based colorization is to…
Few-shot learning with improved local representations via bias rectify module
Chao Dong, Qi Ye, Wenchao Meng +1
Recent approaches based on metric learning have achieved great progress in few-shot learning. However, most of them are limited to image-level representation manners, which fail to…
Temporally Consistent Video Colorization with Deep Feature Propagation and Self-regularization Learning
Yihao Liu, Hengyuan Zhao, Kelvin C. K. Chan +4
Video colorization is a challenging and highly ill-posed problem. Although recent years have witnessed remarkable progress in single image colorization, there is relatively less re…
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution
Liangbin Xie, Xintao Wang, Chao Dong +2
Recent blind super-resolution (SR) methods typically consist of two branches, one for degradation prediction and the other for conditional restoration. However, our experiments sho…
Discovering Distinctive "Semantics" in Super-Resolution Networks
Yihao Liu, Anran Liu, Jinjin Gu +4
Image super-resolution (SR) is a representative low-level vision problem. Although deep SR networks have achieved extraordinary success, we are still unaware of their working mecha…