Area of research
Computer Vision and Pattern Recognition · Computational Mechanics
Research interest
Research interests include Sparse and Compressive Sensing Techniques, Face and Expression Recognition, Advanced Neural Network Applications, and Stochastic Gradient Optimization Techniques.
Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation
Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm
Neural Multimodal Cooperative Learning Toward Micro-Video Understanding
Tensor Low-Rank Representation for Data Recovery and Clustering
Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining
Subspace Clustering by Block Diagonal Representation
On the Applications of Robust PCA in Image and Video Processing
Exact Low Tubal Rank Tensor Recovery from Gaussian Measurements
Tensor Factorization for Low-Rank Tensor Completion
A Unified Alternating Direction Method of Multipliers by Majorization Minimization
Optimized Color Filter Arrays for Sparse Representation-Based Demosaicking
Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization
Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks
Convex Sparse Spectral Clustering: Single-View to Multi-View
Tensor LRR and Sparse Coding-Based Subspace Clustering
Automatic Design of High-Sensitivity Color Filter Arrays With Panchromatic Pixels
Laplacian Regularized Low-Rank Representation and Its Applications
Generalized Singular Value Thresholding
Generalized Nonconvex Nonsmooth Low-Rank Minimization
Robust Estimation of 3D Human Poses from a Single Image
Robust Subspace Segmentation with Block-Diagonal Prior
Proximal Iteratively Reweighted Algorithm with Multiple Splitting for Nonconvex Sparsity Optimization
Correlation Adaptive Subspace Segmentation by Trace Lasso
A comparison of typical ℓ minimization algorithms
Correntropy Induced L2 Graph for Robust Subspace Clustering
Robust Recovery of Subspace Structures by Low-Rank Representation