2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CV2020★ 2 cited
Enhanced nonconvex low-rank approximation of tensor multi-modes for tensor completion
Haijin Zeng, Xiaozhen Xie, Jifeng Ning
Higher-order low-rank tensor arises in many data processing applications and has attracted great interests. Inspired by low-rank approximation theory, researchers have proposed a s…
cs.CV2020
Hyperspectral Image Restoration via Global Total Variation Regularized Local nonconvex Low-Rank matrix Approximation
Haijin Zeng, Xiaozhen Xie, Jifeng Ning
Several bandwise total variation (TV) regularized low-rank (LR)-based models have been proposed to remove mixed noise in hyperspectral images (HSIs). Conventionally, the rank of LR…
cs.CV2020★ 2 cited
Tensor completion using enhanced multiple modes low-rank prior and total variation
Haijin Zeng, Xiaozhen Xie, Jifeng Ning
In this paper, we propose a novel model to recover a low-rank tensor by simultaneously performing double nuclear norm regularized low-rank matrix factorizations to the all-mode mat…