Experiences
I am currently a Professor in the School of Computing and Artificial Intelligence at SWUFE.
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2019: Ph.D. in Mathematics from UESTC, advised by Prof. Ting-Zhu Huang.
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2019: Research Assistant at Hong Kong Baptist University, advised by Prof. Michael Ng.
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2017 - 2018: Visiting Student at Instituto Superior Técnico, advised by Prof. Jose M. Bioucas Dias.
Research Interests
Image Processing
Computer Vision
Machine Learning
Tensor Methods
Hyperspectral Imaging
Publications
Book Chapter
Transform-based tensor singular value decomposition in multidimensional image recovery
Tai-Xiang Jiang, Michael K Ng, Xi-Le Zhao
in Tensors for Data Processing: Theory, Methods and Applications, Elsevier, 2022.
@incollection{jiang2022transform,
title={Transform-based tensor singular value decomposition in multidimensional image recovery},
author={Jiang, Tai-Xiang and Ng, Michael K and Zhao, Xi-Le},
booktitle={Tensors for Data Processing},
pages={31--60},
year={2022},
publisher={Elsevier}
}
Online
DELTA: Deep Low-Rank Tensor Representation for Multi-Dimensional Data Recovery
Guo-Wei Yang, Liqiao Yang, Tai-Xiang Jiang*, Guisong Liu, Michael K Ng
IEEE Transactions on Pattern Analysis and Machine Intelligence
@article{yang2025delta,
title={DELTA: Deep Low-Rank Tensor Representation for Multi-Dimensional Data Recovery},
author={Yang, Guo-Wei and Yang, Liqiao and Jiang, Tai-Xiang and Liu, Guisong and Ng, Michael K},
journal={IEEE transactions on pattern analysis and machine intelligence},
doi={10.1109/TPAMI.2025.3630339},
year={2025}
}
2026
Degradation accordant plug-and-play for low-rank tensor recovery
Yexun Hu, Zixin Tang, Tai-Xiang Jiang*, Xi-Le Zhao, Guisong Liu
Pattern Recognition, 2026.
@article{HU2026112612,
title={Degradation accordant plug-and-play for low-rank tensor recovery},
author={Yexun Hu and Zixin Tang and Tai-Xiang Jiang and Xi-Le Zhao and Guisong Liu},
journal={Pattern Recognition},
volume={172},
pages={112612},
year={2026}
}
2025
PALADIN: a novel plug-and-play 3D CS-MRI reconstruction method
Jia-Mian Wu, Shi-Bai Yin, Tai-Xiang Jiang*, Gui-Song Liu, Xi-Le Zhao
Inverse Problems, 2025.
@article{wu2025paladin,
title={PALADIN: a novel plug-and-play 3D CS-MRI reconstruction method},
author={Wu, Jia-Mian and Yin, Shi-Bai and Jiang, Tai-Xiang and Liu, Gui-Song and Zhao, Xi-Le},
journal={Inverse Problems},
volume={41},
number={3},
pages={035014},
year={2025},
publisher={IOP Publishing}
}Enhancing the Adversarial Robustness via Manifold Projection
Zhiting Li, Shibai Yin, Tai-Xiang Jiang*, Yexun Hu, Jia-Mian Wu, Guowei Yang, Guisong Liu
AAAI, 2025.
@inproceedings{li2025enhancing,
title={Enhancing the Adversarial Robustness via Manifold Projection},
author={Li, Zhiting and Yin, Shibai and Jiang, Tai-Xiang and Hu, Yexun and Wu, Jia-Mian and Yang, Guowei and Liu, Guisong},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={39},
number={1},
pages={451--459},
year={2025}
}Adaptive sampling with tensor leverage scores for exact low-rank third-order tensor completion
Xuan Chen, Tai-Xiang Jiang*, Yexun Hu, Jinjin Yu, Michael K Ng
Applied Mathematical Modelling, 2025.
@article{chen2025adaptive,
title={Adaptive sampling with tensor leverage scores for exact low-rank third-order tensor completion},
author={Chen, Xuan and Jiang, Tai-Xiang and Hu, Yexun and Yu, Jinjin and Ng, Michael K},
journal={Applied Mathematical Modelling},
volume={138},
pages={115744},
year={2025},
publisher={Elsevier}
}Learning a more compact representation for low-rank tensor completion
Xi-Zhuo Li, Liqiao Yang, Tai-Xiang Jiang*, Guisong Liu
Neurocomputing, 2025.
@article{li2025learning,
title={Learning a more compact representation for low-rank tensor completion},
author={Li, Xi-Zhuo and Jiang, Tai-Xiang and Yang, Liqiao and Liu, Guisong},
journal={Neurocomputing},
volume={617},
pages={129036},
year={2025},
publisher={Elsevier}
}Fourier single-pixel spectral imaging via local low-rank tensor nuclear norm and deep tensor priors
Zixin Tang, Yexun Hu, Chen Duo, Guowei Yang, Taixiang Jiang*, Daqing Guo*
Optics Letters, 2025.
@article{tang2025fourier,
title={Fourier single-pixel spectral imaging via local low-rank tensor nuclear norm and deep tensor priors},
author={Tang, Zixin and Hu, Yexun and Duo, Chen and Yang, Guowei and Jiang, Taixiang and Guo, Daqing},
journal={Optics Letters},
volume={50},
number={4},
pages={1281--1284},
year={2025},
publisher={Optica Publishing Group}
}Spectral Low-Rank Attention with Flow-Based Refinement for Spectral Reconstruction
Yiwen Wang, Zixin Tang, Yexun Hu*, Guisong Liu, Tai-Xiang Jiang
ICASSP, 2025.
@inproceedings{wang2025spectral,
title={Spectral Low-Rank Attention with Flow-Based Refinement for Spectral Reconstruction},
author={Wang, Yiwen and Tang, Zixin and Hu, Yexun and Liu, Guisong and Jiang, Tai-Xiang},
booktitle={ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={1--5},
year={2025},
organization={IEEE}
}Model-Guided Stock Movements Prediction with Homogeneous–Heterogeneous pattern learning
Yi Zhou, Tai-Xiang Jiang, Jun Wang*, Jinghua Tan*
Applied Soft Computing, 2025.
@article{zhou2025model,
title={Model-Guided Stock Movements Prediction with Homogeneous--Heterogeneous pattern learning},
author={Zhou, Yi and Jiang, Tai-Xiang and Wang, Jun and Tan, Jinghua},
journal={Applied Soft Computing},
volume={182},
pages={113519},
year={2025},
publisher={Elsevier}
}Efficient FCTN Decomposition with Structural Sparsity for Noisy Tensor Completion
Wei-Jian Huang, Li Huang, Tai-Xiang Jiang*, Yu-Bang Zheng*, Guisong Liu
IEEE Transactions on Big Data, 2025.
@article{huang2025efficient,
author={Huang, Wei-Jian and Huang, Li and Jiang, Tai-Xiang and Zheng, Yu-Bang and Liu, Guisong},
journal={IEEE Transactions on Big Data},
title={Efficient FCTN Decomposition With Structural Sparsity for Noisy Tensor Completion},
year={2025},
volume={11},
number={6},
pages={3225-3239}
}
2024
CoNoT: Coupled nonlinear transform-based low-rank tensor representation for multidimensional image completion
Jian-Li Wang, Ting-Zhu Huang, Xi-Le Zhao, Yi-Si Luo, Tai-Xiang Jiang
IEEE Transactions on Neural Networks and Learning Systems, 2024.
@article{wang2024conot,
title={CoNoT: Coupled nonlinear transform-based low-rank tensor representation for multidimensional image completion},
author={Wang, Jian-Li and Huang, Ting-Zhu and Zhao, Xi-Le and Luo, Yi-Si and Jiang, Tai-Xiang},
journal={IEEE Transactions on Neural Networks and Learning Systems},
volume={35},
number={7},
pages={8969--8983},
year={2024},
publisher={IEEE}
}Learnable Transform-Assisted Tensor Decomposition for Spatio-Irregular Multidimensional Data Recovery
Hao Zhang, Ting-Zhu Huang, Xi-Le Zhao, Shuqin Zhang, Jin-Yu Xie, Tai-Xiang Jiang, Michael K Ng
ACM Transactions on Knowledge Discovery from Data, 2024.
@article{zhang2024learnable,
title={Learnable Transform-Assisted Tensor Decomposition for Spatio-Irregular Multidimensional Data Recovery},
author={Zhang, Hao and Huang, Ting-Zhu and Zhao, Xi-Le and Zhang, Shuqin and Xie, Jin-Yu and Jiang, Tai-Xiang and Ng, Michael K},
journal={ACM Transactions on Knowledge Discovery from Data},
volume={19},
number={1},
pages={1--23},
year={2024},
publisher={ACM New York, NY}
}Unsupervised video rain streaks removal with deep foreground–background modeling
Jun-Hao Zhuang, Yi-Si Luo, Xi-Le Zhao, Tai-Xiang Jiang, Yi Chang, Jun Liu
Journal of Computational and Applied Mathematics, 2024.
@article{zhuang2024unsupervised,
title={Unsupervised video rain streaks removal with deep foreground--background modeling},
author={Zhuang, Jun-Hao and Luo, Yi-Si and Zhao, Xi-Le and Jiang, Tai-Xiang and Chang, Yi and Liu, Jun},
journal={Journal of Computational and Applied Mathematics},
volume={436},
pages={115431},
year={2024},
publisher={North-Holland}
}A guidable nonlocal low-rank approximation model for hyperspectral image denoising
Yong Chen, Juan Zhang, Jinshan Zeng, Wenzhen Lai, Xinfeng Gui, Tai-Xiang Jiang
Signal Processing, 2024.
@article{chen2024guidable,
title={A guidable nonlocal low-rank approximation model for hyperspectral image denoising},
author={Chen, Yong and Zhang, Juan and Zeng, Jinshan and Lai, Wenzhen and Gui, Xinfeng and Jiang, Tai-Xiang},
journal={Signal Processing},
volume={215},
pages={109266},
year={2024},
publisher={Elsevier}
}Incremental algorithms for truncated higher-order singular value decompositions
Chao Zeng, Michael K Ng, Tai-Xiang Jiang*
BIT Numerical Mathematics, 2024.
@article{zeng2024incremental,
title={Incremental algorithms for truncated higher-order singular value decompositions},
author={Zeng, Chao and Ng, Michael K and Jiang, Tai-Xiang},
journal={BIT Numerical Mathematics},
volume={64},
number={1},
pages={4},
year={2024},
publisher={Springer}
}The Generalized Tensor Decomposition with Heterogeneous Tensor Product for Third-Order Tensors
Yun-Yang Liu, Xi-Le Zhao, Meng Ding, Jianjun Wang, Tai-Xiang Jiang, Ting-Zhu Huang
Journal of Scientific Computing, 2024.
@article{liu2024generalized,
title={The Generalized Tensor Decomposition with Heterogeneous Tensor Product for Third-Order Tensors},
author={Liu, Yun-Yang and Zhao, Xi-Le and Ding, Meng and Wang, Jianjun and Jiang, Tai-Xiang and Huang, Ting-Zhu},
journal={Journal of Scientific Computing},
volume={100},
number={3},
pages={78},
year={2024},
publisher={Springer}
}Fast Large-Scale Hyperspectral Image Denoising via Non-Iterative Low-Rank Subspace Representation
Yong Chen, Jinshan Zeng, Wei He, Xi-Le Zhao, Tai-Xiang Jiang, Qing Huang
IEEE Transactions on Geoscience and Remote Sensing, 2024.
@article{chen2024fast,
title={Fast Large-Scale Hyperspectral Image Denoising via Non-Iterative Low-Rank Subspace Representation},
author={Chen, Yong and Zeng, Jinshan and He, Wei and Zhao, Xi-Le and Jiang, Tai-Xiang and Huang, Qing},
journal={IEEE Transactions on Geoscience and Remote Sensing},
year={2024},
publisher={IEEE}
}
2023
Dictionary learning with low-rank coding coefficients for tensor completion
Tai-Xiang Jiang, Xi-Le Zhao, Hao Zhang, Michael K Ng
IEEE Transactions on Neural Networks and Learning Systems, 2023.
@article{jiang2023dictionary,
title={Dictionary learning with low-rank coding coefficients for tensor completion},
author={Jiang, Tai-Xiang and Zhao, Xi-Le and Zhang, Hao and Ng, Michael K},
journal={IEEE Transactions on Neural Networks and Learning Systems},
volume={34},
number={2},
pages={932--946},
year={2023},
publisher={IEEE}
}Nonnegative low rank tensor approximations with multidimensional image applications
Tai-Xiang Jiang, Michael K Ng, Junjun Pan, Guang-Jing Song
Numerische Mathematik, 2023.
@article{jiang2023nonnegative,
title={Nonnegative low rank tensor approximations with multidimensional image applications},
author={Jiang, Tai-Xiang and Ng, Michael K and Pan, Junjun and Song, Guang-Jing},
journal={Numerische Mathematik},
volume={153},
number={1},
pages={141--170},
year={2023},
publisher={Springer Berlin Heidelberg Berlin/Heidelberg}
}Tangent space based alternating projections for nonnegative low rank matrix approximation
Guangjing Song, Michael K Ng, Tai-Xiang Jiang*
IEEE Transactions on Knowledge and Data Engineering, 2023.
@article{song2023tangent,
title={Tangent space based alternating projections for nonnegative low rank matrix approximation},
author={Song, Guangjing and Ng, Michael K and Jiang, Tai-Xiang},
journal={IEEE Transactions on Knowledge and Data Engineering},
year={2023},
publisher={IEEE}
}Superpixel-oriented thick cloud removal method for multitemporal remote sensing images
Qin Jiang, Xi-Le Zhao, Jie Lin, Jing-Hua Yang, Jiangtao Peng, Tai-Xiang Jiang
IEEE Geoscience and Remote Sensing Letters, 2023.
@article{jiang2023superpixel,
title={Superpixel-oriented thick cloud removal method for multitemporal remote sensing images},
author={Jiang, Qin and Zhao, Xi-Le and Lin, Jie and Yang, Jing-Hua and Peng, Jiangtao and Jiang, Tai-Xiang},
journal={IEEE Geoscience and Remote Sensing Letters},
volume={21},
pages={1--5},
year={2023},
publisher={IEEE}
}Essential tensor learning for multimodal information-driven stock movement prediction
Jun Wang, Yexun Hu, Tai-Xiang Jiang*, Jinghua Tan*, Qing Li
Knowledge-Based Systems, 2023.
@article{wang2023essential,
title={Essential tensor learning for multimodal information-driven stock movement prediction},
author={Wang, Jun and Hu, Yexun and Jiang, Tai-Xiang and Tan, Jinghua and Li, Qing},
journal={Knowledge-Based Systems},
volume={262},
pages={110262},
year={2023},
publisher={Elsevier}
}Tangent space based alternating projections for nonnegative low rank matrix approximation
Guangjing Song, Michael K Ng, Tai-Xiang Jiang*
IEEE Transactions on Knowledge and Data Engineering, 2023.
@article{song2023tangent,
title={Tangent space based alternating projections for nonnegative low rank matrix approximation},
author={Song, Guangjing and Ng, Michael K and Jiang, Tai-Xiang},
journal={IEEE Transactions on Knowledge and Data Engineering},
year={2023},
publisher={IEEE}
}GuidedNet: A general CNN fusion framework via high-resolution guidance for hyperspectral image super-resolution
Ran Ran, Liang-Jian Deng, Tai-Xiang Jiang, Jin-Fan Hu, Jocelyn Chanussot, Gemine Vivone
IEEE Transactions on Cybernetics, 2023.
@article{ran2023guidednet,
title={GuidedNet: A general CNN fusion framework via high-resolution guidance for hyperspectral image super-resolution},
author={Ran, Ran and Deng, Liang-Jian and Jiang, Tai-Xiang and Hu, Jin-Fan and Chanussot, Jocelyn and Vivone, Gemine},
journal={IEEE Transactions on Cybernetics},
volume={53},
number={7},
pages={4148--4161},
year={2023},
publisher={IEEE}
}
2022
Tensor completion via complementary global, local, and nonlocal priors ESI Highly Cited
Xi-Le Zhao, Jing-Hua Yang, Tian-Hui Ma, Tai-Xiang Jiang*, Michael K Ng, Ting-Zhu Huang
IEEE Transactions on Image Processing, 2021.
@article{zhao2021tensor,
title={Tensor completion via complementary global, local, and nonlocal priors},
author={Zhao, Xi-Le and Yang, Jing-Hua and Ma, Tian-Hui and Jiang, Tai-Xiang and Ng, Michael K and Huang, Ting-Zhu},
journal={IEEE Transactions on Image Processing},
volume={31},
pages={984--999},
year={2021},
publisher={IEEE}
}Adaptive hyperspectral mixed noise removal
Tai-Xiang Jiang, Lina Zhuang*, Ting-Zhu Huang, Xi-Le Zhao, Jos{\'e} M Bioucas-Dias
IEEE Transactions on Geoscience and Remote Sensing, 2022.
@article{jiang2022adaptive,
title={Adaptive hyperspectral mixed noise removal},
author={Jiang, Tai-Xiang and Zhuang, Lina and Huang, Ting-Zhu and Zhao, Xi-Le and Bioucas-Dias, Jos{\'e} M},
journal={IEEE Transactions on Geoscience and Remote Sensing},
year={2022},
publisher={IEEE}
}HLRTF: Hierarchical Low-Rank Tensor Factorization for Inverse Problems in Multi-Dimensional Imaging
Yisi Luo, Xi-Le Zhao, Deyu Meng, Tai-Xiang Jiang
CVPR, 2022.
@inproceedings{luo2022hlrtf,
title={HLRTF: Hierarchical Low-Rank Tensor Factorization for Inverse Problems in Multi-Dimensional Imaging},
author={Luo, Yisi and Zhao, Xi-Le and Meng, Deyu and Jiang, Tai-Xiang},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={19303--19312},
year={2022}
}Self-supervised nonlinear transform-based tensor nuclear norm for multi-dimensional image recovery
Yi-Si Luo, Xi-Le Zhao, Tai-Xiang Jiang, Yi Chang, Michael K Ng, Chao Li
IEEE Transactions on Image Processing, 2022.
@article{luo2022self,
title={Self-supervised nonlinear transform-based tensor nuclear norm for multi-dimensional image recovery},
author={Luo, Yi-Si and Zhao, Xi-Le and Jiang, Tai-Xiang and Chang, Yi and Ng, Michael K and Li, Chao},
journal={IEEE Transactions on Image Processing},
volume={31},
pages={3793--3808},
year={2022},
publisher={IEEE}
}SelfS2: Self-Supervised Transfer Learning for Sentinel-2 Multispectral Image Super-Resolution
Xiao Qian, Tai-Xiang Jiang*, Xi-Le Zhao
IEEE J-STARS, 2022.
@article{qian2022selfs2,
title={SelfS2: Self-Supervised Transfer Learning for Sentinel-2 Multispectral Image Super-Resolution},
author={Qian, Xiao and Jiang, Tai-Xiang and Zhao, Xi-Le},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
volume={16},
pages={215--227},
year={2022},
publisher={IEEE}
}LAGConv: Local-Context Adaptive Convolution Kernels with Global Harmonic Bias for Pansharpening
Zi-Rong Jin, Tian-Jing Zhang, Tai-Xiang Jiang, Gemine Vivone, Liang-Jian Deng
AAAI, 2022.
@inproceedings{jin2022lagconv,
title={LAGConv: Local-Context Adaptive Convolution Kernels with Global Harmonic Bias for Pansharpening},
author={Jin, Zi-Rong and Zhang, Tian-Jing and Jiang, Tai-Xiang and Vivone, Gemine and Deng, Liang-Jian},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={36},
number={1},
pages={1113--1121},
year={2022}
}UConNet: Unsupervised Controllable Network for Image and Video Deraining
Junhao Zhuang, Yisi Luo, Xile Zhao, Taixiang Jiang, Bichuan Guo
ACM MM, 2022.
@inproceedings{zhuang2022uconnet,
title={UConNet: Unsupervised Controllable Network for Image and Video Deraining},
author={Zhuang, Junhao and Luo, Yisi and Zhao, Xile and Jiang, Taixiang and Guo, Bichuan},
booktitle={Proceedings of the 30th ACM International Conference on Multimedia},
pages={5436--5445},
year={2022}
}
2021
A tensor subspace representation-based method for hyperspectral image denoising
Jie Lin, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang, Lina Zhuang
IEEE Transactions on Geoscience and Remote Sensing, 2021.
@article{lin2021tensor,
title={A tensor subspace representation-based method for hyperspectral image denoising},
author={Lin, Jie and Huang, Ting-Zhu and Zhao, Xi-Le and Jiang, Tai-Xiang and Zhuang, Lina},
journal={IEEE Transactions on Geoscience and Remote Sensing},
volume={59},
number={9},
pages={7739--7757},
year={2021},
publisher={IEEE}
}An approximation method of CP rank for third-order tensor completion
Chao Zeng, Tai-Xiang Jiang, Michael K Ng
Numerische Mathematik, 2021.
@article{zeng2021approximation,
title={An approximation method of CP rank for third-order tensor completion},
author={Zeng, Chao and Jiang, Tai-Xiang and Ng, Michael K},
journal={Numerische Mathematik},
volume={147},
number={3},
pages={727--757},
year={2021},
publisher={Springer Berlin Heidelberg}
}Fully-connected tensor network decomposition and its application to higher-order tensor completion
Yu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao, Qibin Zhao, Tai-Xiang Jiang
AAAI, 2021.
@inproceedings{zheng2021fully,
title={Fully-connected tensor network decomposition and its application to higher-order tensor completion},
author={Zheng, Yu-Bang and Huang, Ting-Zhu and Zhao, Xi-Le and Zhao, Qibin and Jiang, Tai-Xiang},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={35},
number={12},
pages={11071--11078},
year={2021}
}Multi-Dimensional Visual Data Completion via Low-Rank Tensor Representation Under Coupled Transform
Jian-Li Wang, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang, Michael K Ng
IEEE Transactions on Image Processing, 2021.
@article{wang2021multi,
title={Multi-Dimensional Visual Data Completion via Low-Rank Tensor Representation Under Coupled Transform},
author={Wang, Jian-Li and Huang, Ting-Zhu and Zhao, Xi-Le and Jiang, Tai-Xiang and Ng, Michael K},
journal={IEEE Transactions on Image Processing},
volume={30},
pages={3581--3596},
year={2021},
publisher={IEEE}
}A novel non-convex low-rank tensor approximation model for hyperspectral image restoration
Jie Lin, Ting-Zhu Huang, Xi-Le Zhao, Tian-Hui Ma, Tai-Xiang Jiang, Yu-Bang Zheng
Applied Mathematics and Computation, 2021.
@article{lin2021novel,
title={A novel non-convex low-rank tensor approximation model for hyperspectral image restoration},
author={Lin, Jie and Huang, Ting-Zhu and Zhao, Xi-Le and Ma, Tian-Hui and Jiang, Tai-Xiang and Zheng, Yu-Bang},
journal={Applied Mathematics and Computation},
volume={408},
pages={126342},
year={2021},
publisher={Elsevier}
}Hyperspectral image super-resolution via deep spatiospectral attention convolutional neural networks
Jin-Fan Hu, Ting-Zhu Huang, Liang-Jian Deng, Tai-Xiang Jiang, Gemine Vivone, Jocelyn Chanussot
IEEE Transactions on Neural Networks and Learning Systems, 2021.
@article{hu2021hyperspectral,
title={Hyperspectral image super-resolution via deep spatiospectral attention convolutional neural networks},
author={Hu, Jin-Fan and Huang, Ting-Zhu and Deng, Liang-Jian and Jiang, Tai-Xiang and Vivone, Gemine and Chanussot, Jocelyn},
journal={IEEE Transactions on Neural Networks and Learning Systems},
volume={33},
number={12},
pages={7251--7265},
year={2021},
publisher={IEEE}
}Multiscale feature tensor train rank minimization for multidimensional image recovery
Hao Zhang, Xi-Le Zhao, Tai-Xiang Jiang, Michael K Ng, Ting-Zhu Huang
IEEE Transactions on Cybernetics, 2021.
@article{zhang2021multiscale,
title={Multiscale feature tensor train rank minimization for multidimensional image recovery},
author={Zhang, Hao and Zhao, Xi-Le and Jiang, Tai-Xiang and Ng, Michael K and Huang, Ting-Zhu},
journal={IEEE Transactions on Cybernetics},
volume={52},
number={12},
pages={13395--13410},
year={2021},
publisher={IEEE}
}
2020
Framelet Representation of Tensor Nuclear Norm for Third-Order Tensor Completion
Tai-Xiang Jiang, Michael K Ng, Xi-Le Zhao, Ting-zhu Huang
IEEE Transactions on Image Processing, 2020.
@article{jiang2020framelet,
title={Framelet Representation of Tensor Nuclear Norm for Third-Order Tensor Completion},
author={Jiang, Tai-Xiang and Ng, Michael, K. and Zhao, Xi-Le and Huang, Ting-zhu},
journal={IEEE Transactions on Image Processing},
volume={29},
pages={7233--7244},
year={2020},
publisher={IEEE}
}Multi-dimensional imaging data recovery via minimizing the partial sum of tubal nuclear norm ESI Highly Cited
Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng
Journal of Computational and Applied Mathematics, 2020.
@article{jiang2020multi,
title={Multi-dimensional imaging data recovery via minimizing the partial sum of tubal nuclear norm},
author={Jiang, Tai-Xiang and Huang, Ting-Zhu and Zhao, Xi-Le and Deng, Liang-Jian},
journal={Journal of Computational and Applied Mathematics},
volume={372},
pages={112680},
year={2020},
publisher={Elsevier}
}Tensor N-tubal rank and its convex relaxation for low-rank tensor recovery
Yu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang, Teng-Yu Ji, Tian-Hui Ma
Information Sciences, 2020.
@article{zheng2020tensor,
title={Tensor N-tubal rank and its convex relaxation for low-rank tensor recovery},
author={Zheng, Yu-Bang and Huang, Ting-Zhu and Zhao, Xi-Le and Jiang, Tai-Xiang and Ji, Teng-Yu and Ma, Tian-Hui},
journal={Information Sciences},
volume={532},
pages={170--189},
year={2020},
publisher={Elsevier}
}Mixed noise removal in hyperspectral image via low-fibered-rank regularization
Yu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang, Tian-Hui Ma, Teng-Yu Ji
IEEE Transactions on Geoscience and Remote Sensing, 2020.
@article{zheng2020mixed,
title={Mixed noise removal in hyperspectral image via low-fibered-rank regularization},
author={Zheng, Yu-Bang and Huang, Ting-Zhu and Zhao, Xi-Le and Jiang, Tai-Xiang and Ma, Tian-Hui and Ji, Teng-Yu},
journal={IEEE Transactions on Geoscience and Remote Sensing},
volume={58},
number={1},
pages={734--749},
year={2020},
publisher={IEEE}
}Video deraining via nonlocal low-rank regularization
Yugang Wang, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang
Applied Mathematical Modelling, 2020.
@article{wang2020video,
title={Video deraining via nonlocal low-rank regularization},
author={Wang, Yugang and Huang, Ting-Zhu and Zhao, Xi-Le and Jiang, Tai-Xiang},
journal={Applied Mathematical Modelling},
volume={79},
pages={896--913},
year={2020},
publisher={Elsevier}
}Deep plug-and-play prior for low-rank tensor completion
Xi-Le Zhao, Wen-Hao Xu, Tai-Xiang Jiang*, Yao Wang, Michael K Ng
Neurocomputing, 2020.
@article{zhao2020deep,
title={Deep plug-and-play prior for low-rank tensor completion},
author={Zhao, Xi-Le and Xu, Wen-Hao and Jiang, Tai-Xiang and Wang, Yao and Ng, Michael K},
journal={Neurocomputing},
volume={400},
pages={137--149},
year={2020},
publisher={Elsevier}
}Fast algorithm with theoretical guarantees for constrained low-tubal-rank tensor recovery in hyperspectral images denoising
Xi-Le Zhao, Hao Zhang, Tai-Xiang Jiang, Michael K Ng, Xiong-Jun Zhang
Neurocomputing, 2020.
@article{zhao2020fast,
title={Fast algorithm with theoretical guarantees for constrained low-tubal-rank tensor recovery in hyperspectral images denoising},
author={Zhao, Xi-Le and Zhang, Hao and Jiang, Tai-Xiang and Ng, Michael K and Zhang, Xiong-Jun},
journal={Neurocomputing},
volume={413},
pages={397--409},
year={2020},
publisher={Elsevier}
}
2019
FastDeRain: A novel video rain streak removal method using directional gradient priors ESI Highly Cited
Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Yao Wang
IEEE Transactions on Image Processing, 2019.
@article{jiang2019fastderain,
title={FastDeRain: A novel video rain streak removal method using directional gradient priors},
author={Jiang, Tai-Xiang and Huang, Ting-Zhu and Zhao, Xi-Le and Deng, Liang-Jian and Wang, Yao},
journal={IEEE Transactions on Image Processing},
volume={28},
number={4},
pages={2089--2102},
year={2019},
publisher={IEEE}
}A total variation and group sparsity based tensor optimization model for video rain streak removal
Ye-Tao Wang, Xi-Le Zhao*, Tai-Xiang Jiang*, Liang-Jian Deng, Tian-Hui Ma, Yue-Tian Zhang, Ting-Zhu Huang
Signal Processing: Image Communication, 2019.
@article{wang2019total,
title={A total variation and group sparsity based tensor optimization model for video rain streak removal},
author={Wang, Ye-Tao and Zhao, Xi-Le and Jiang, Tai-Xiang and Deng, Liang-Jian and Ma, Tian-Hui and Zhang, Yue-Tian and Huang, Ting-Zhu},
journal={Signal Processing: Image Communication},
volume={73},
pages={96--108},
year={2019},
publisher={Elsevier}
}Low-rank tensor completion via smooth matrix factorization
Yu-Bang Zheng, Ting-Zhu Huang, Teng-Yu Ji, Xi-Le Zhao, Tai-Xiang Jiang, Tian-Hui Ma
Applied Mathematical Modelling, 2019.
@article{zheng2019low,
title={Low-rank tensor completion via smooth matrix factorization},
author={Zheng, Yu-Bang and Huang, Ting-Zhu and Ji, Teng-Yu and Zhao, Xi-Le and Jiang, Tai-Xiang and Ma, Tian-Hui},
journal={Applied Mathematical Modelling},
volume={70},
pages={677--695},
year={2019},
publisher={Elsevier}
}Low-rank tensor completion via combined non-local self-similarity and low-rank regularization
Xiao-Tong Li, Xi-Le Zhao, Tai-Xiang Jiang, Yu-Bang Zheng, Teng-Yu Ji, Ting-Zhu Huang
Neurocomputing, 2019.
@article{li2019low,
title={Low-rank tensor completion via combined non-local self-similarity and low-rank regularization},
author={Li, Xiao-Tong and Zhao, Xi-Le and Jiang, Tai-Xiang and Zheng, Yu-Bang and Ji, Teng-Yu and Huang, Ting-Zhu},
journal={Neurocomputing},
volume={367},
pages={1--12},
year={2019},
publisher={Elsevier}
}
2018
Matrix factorization for low-rank tensor completion using framelet prior
Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Teng-Yu Ji, Liang-Jian Deng
Information Sciences, 2018.
@article{jiang2018matrix,
title={Matrix factorization for low-rank tensor completion using framelet prior},
author={Jiang, Tai-Xiang and Huang, Ting-Zhu and Zhao, Xi-Le and Ji, Teng-Yu and Deng, Liang-Jian},
journal={Information Sciences},
volume={436},
pages={403--417},
year={2018},
publisher={Elsevier}
}A directional global sparse model for single image rain removal
Liang-Jian Deng, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang
Applied Mathematical Modelling, 2018.
@article{deng2018directional,
title={A directional global sparse model for single image rain removal},
author={Deng, Liang-Jian and Huang, Ting-Zhu and Zhao, Xi-Le and Jiang, Tai-Xiang},
journal={Applied Mathematical Modelling},
volume={59},
pages={662--679},
year={2018},
publisher={Elsevier}
}
2017
A novel tensor-based video rain streaks removal approach via utilizing discriminatively intrinsic priors
Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Yao Wang
CVPR, 2017.
@inproceedings{jiang2017novel,
title={A novel tensor-based video rain streaks removal approach via utilizing discriminatively intrinsic priors},
author={Jiang, Tai-Xiang and Huang, Ting-Zhu and Zhao, Xi-Le and Deng, Liang-Jian and Wang, Yao},
booktitle={Proceedings of the ieee conference on computer vision and pattern recognition},
pages={4057--4066},
year={2017}
}