58 citations · 112 across the 10 of their papers we have counts for
6 papers · 1 filter
Robust Phase Retrieval with Green Noise Binary Masks
Qiuliang Ye, Yuk-Hee Chan, Michael G. Somekh +1
Phase retrieval with pre-defined optical masks can provide extra constraint and thus achieve improved performance. The recent progress in optimization theory demonstrates the super…
Enhancing and Learning Denoiser without Clean Reference
Rui Zhao, Daniel P. K. Lun, Kin-Man Lam
Recent studies on learning-based image denoising have achieved promising performance on various noise reduction tasks. Most of these deep denoisers are trained either under the sup…
DeepGIN: Deep Generative Inpainting Network for Extreme Image Inpainting
Chu-Tak Li, Wan-Chi Siu, Zhi-Song Liu +2
The degree of difficulty in image inpainting depends on the types and sizes of the missing parts. Existing image inpainting approaches usually encounter difficulties in completing…
Deep Relighting Networks for Image Light Source Manipulation
Li-Wen Wang, Wan-Chi Siu, Zhi-Song Liu +2
Manipulating the light source of given images is an interesting task and useful in various applications, including photography and cinematography. Existing methods usually require…
Deep Multi-task Learning for Facial Expression Recognition and Synthesis Based on Selective Feature Sharing
Rui Zhao, Tianshan Liu, Jun Xiao +2
Multi-task learning is an effective learning strategy for deep-learning-based facial expression recognition tasks. However, most existing methods take into limited consideration th…
Enhancement of a CNN-Based Denoiser Based on Spatial and Spectral Analysis
Rui Zhao, Kin-Man Lam, Daniel P. K. Lun
Convolutional neural network (CNN)-based image denoising methods have been widely studied recently, because of their high-speed processing capability and good visual quality. Howev…