activity
20152021
most citedSingle image super-resolution by approximated Heaviside functions

3 citations · 9 across the 6 of their papers we have counts for

collaborators

14 papers

cs.CV20213 cited

Nonlinear Transform Induced Tensor Nuclear Norm for Tensor Completion

Ben-Zheng Li, Xi-Le Zhao, Teng-Yu Ji +2

The linear transform-based tensor nuclear norm (TNN) methods have recently obtained promising results for tensor completion. The main idea of this type of methods is exploiting the…

cs.CV2021

Fully-Connected Tensor Network Decomposition for Robust Tensor Completion Problem

Yun-Yang Liu, Xi-Le Zhao, Guang-Jing Song +2

The robust tensor completion (RTC) problem, which aims to reconstruct a low-rank tensor from partially observed tensor contaminated by a sparse tensor, has received increasing atte…

eess.SP2020

Hyperspectral Super-Resolution via Interpretable Block-Term Tensor Modeling

Meng Ding, Xiao Fu, Ting-Zhu Huang +2

This work revisits coupled tensor decomposition (CTD)-based hyperspectral super-resolution (HSR). HSR aims at fusing a pair of hyperspectral and multispectral images to recover a s…

eess.IV20203 cited

Hyperspectral Image Super-resolution via Deep Spatio-spectral Convolutional Neural Networks

Jin-Fan Hu, Ting-Zhu Huang, Liang-Jian Deng +3

Hyperspectral images are of crucial importance in order to better understand features of different materials. To reach this goal, they leverage on a high number of spectral bands.…

math.NA2020

Fast second-order implicit difference schemes for time distributed-order and Riesz space fractional diffusion-wave equations

Huan-Yan Jian, Ting-Zhu Huang, Xian-Ming Gu +2

In this paper, fast numerical methods are established for solving a class of time distributed-order and Riesz space fractional diffusion-wave equations. We derive new difference sc…

cs.CV2020

Tensor completion via nonconvex tensor ring rank minimization with guaranteed convergence

Meng Ding, Ting-Zhu Huang, Xi-Le Zhao +1

In recent studies, the tensor ring (TR) rank has shown high effectiveness in tensor completion due to its ability of capturing the intrinsic structure within high-order tensors. A…