174 citations · 297 across the 6 of their papers we have counts for
6 papers
Exponential-Family Tensor Completion via Nonconvex Dual Total-Variation Regularization
Wenfei Cao, Yang Chen, Qibin Zhao +2
With the emergence of various tensor data, tensor completion from partial measurements has attracted widespread attention in data science and signal processing. Total Variation (TV…
Proximal PanNet: A Model-Based Deep Network for Pansharpening
Xiangyong Cao, Yang Chen, Wenfei Cao
Recently, deep learning techniques have been extensively studied for pansharpening, which aims to generate a high resolution multispectral (HRMS) image by fusing a low resolution m…
Super-resolution reconstruction of hyperspectral images via low rank tensor modeling and total variation regularization
Shiying He, Haiwei Zhou, Yao Wang +2
In this paper, we propose a novel approach to hyperspectral image super-resolution by modeling the global spatial-and-spectral correlation and local smoothness properties over hype…
Convergence of multi-block Bregman ADMM for nonconvex composite problems
Fenghui Wang, Wenfei Cao, Zongben Xu
The alternating direction method with multipliers (ADMM) has been one of most powerful and successful methods for solving various composite problems. The convergence of the convent…
Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
Jian Sun, Wenfei Cao, Zongben Xu +1
In this paper, we address the problem of estimating and removing non-uniform motion blur from a single blurry image. We propose a deep learning approach to predicting the probabili…
Total Variation Regularized Tensor RPCA for Background Subtraction from Compressive Measurements
Wenfei Cao, Yao Wang, Jian Sun +4
Background subtraction has been a fundamental and widely studied task in video analysis, with a wide range of applications in video surveillance, teleconferencing and 3D modeling.…