activity
20182026
most citedHyperspectral Denoising Using Unsupervised Disentangled Spatio-Spectral Deep Priors

63 citations · 99 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2026

Tensor Decomposition Structure Search Framework from an Interaction Perspective

Ting-Wei Zhou, Xi-Le Zhao, Sheng Liu +3

Recently, tensor decompositions have attracted increasing attention. Fundamentally, different interactions among factors induce distinct tensor decomposition structures (i.e., tens…

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…

cs.CV2021★ 29 cited

Nonlocal Patch-Based Fully-Connected Tensor Network Decomposition for Remote Sensing Image Inpainting

Wen-Jie Zheng, Xi-Le Zhao, Yu-Bang Zheng +1

Remote sensing image (RSI) inpainting plays an important role in real applications. Recently, fully-connected tensor network (FCTN) decomposition has been shown the remarkable abil…

cs.CV2020

Unsupervised Hyperspectral Mixed Noise Removal Via Spatial-Spectral Constrained Deep Image Prior

Yi-Si Luo, Xi-Le Zhao, Tai-Xiang Jiang +2

Recently, convolutional neural network (CNN)-based methods are proposed for hyperspectral images (HSIs) denoising. Among them, unsupervised methods such as the deep image prior (DI…

cs.CV2018★ 7 cited

Tensor N-tubal rank and its convex relaxation for low-rank tensor recovery

Yu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao +3

As low-rank modeling has achieved great success in tensor recovery, many research efforts devote to defining the tensor rank. Among them, the recent popular tensor tubal rank, defi…