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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…
A New Journey from SDRTV to HDRTV
Xiangyu Chen, Zhengwen Zhang, Jimmy S. Ren +3
Nowadays modern displays are capable to render video content with high dynamic range (HDR) and wide color gamut (WCG). However, most available resources are still in standard dynam…
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
Xintao Wang, Liangbin Xie, Chao Dong +1
Though many attempts have been made in blind super-resolution to restore low-resolution images with unknown and complex degradations, they are still far from addressing general rea…