most citedDouble Weighted Truncated Nuclear Norm Regularization for Low-Rank Matrix Completion

11 citations · 15 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2019★ 4 cited

Truncated nuclear norm regularization for low-rank tensor completion

Shengke Xue, Wenyuan Qiu, Fan Liu +1

Recently, low-rank tensor completion has become increasingly attractive in recovering incomplete visual data. Considering a color image or video as a three-dimensional (3D) tensor,…

cs.CV2019★ 11 cited

Double Weighted Truncated Nuclear Norm Regularization for Low-Rank Matrix Completion

Shengke Xue, Wenyuan Qiu, Fan Liu +1

Matrix completion focuses on recovering a matrix from a small subset of its observed elements, and has already gained cumulative attention in computer vision. Many previous approac…