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08/30/2023
Low-Rank Multitask Learning based on Tensorized SVMs and LSSVMs
Multitask learning (MTL) leverages task-relatedness to enhance performan...
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08/22/2023
Tensor Regression
Regression analysis is a key area of interest in the field of data analy...
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08/09/2023
Feature Modulation Transformer: Cross-Refinement of Global Representation via High-Frequency Prior for Image Super-Resolution
Transformer-based methods have exhibited remarkable potential in single ...
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05/13/2023
Illumination-insensitive Binary Descriptor for Visual Measurement Based on Local Inter-patch Invariance
Binary feature descriptors have been widely used in various visual measu...
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05/10/2023
Level-line Guided Edge Drawing for Robust Line Segment Detection
Line segment detection plays a cornerstone role in computer vision tasks...
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05/01/2023
Adaptively Topological Tensor Network for Multi-view Subspace Clustering
Multi-view subspace clustering methods have employed learned self-repres...
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04/29/2023
A Comprehensive Review of Image Line Segment Detection and Description: Taxonomies, Comparisons, and Challenges
Detection and description of line segments lay the basis for numerous vi...
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03/22/2023
Low Rank Optimization for Efficient Deep Learning: Making A Balance between Compact Architecture and Fast Training
Deep neural networks have achieved great success in many data processing...
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03/04/2023
Tensorized LSSVMs for Multitask Regression
Multitask learning (MTL) can utilize the relatedness between multiple ta...
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12/19/2022
FedTADBench: Federated Time-Series Anomaly Detection Benchmark
Time series anomaly detection strives to uncover potential abnormal beha...
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12/14/2022
Deep Negative Correlation Classification
Ensemble learning serves as a straightforward way to improve the perform...
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10/23/2022
Tucker-O-Minus Decomposition for Multi-view Tensor Subspace Clustering
With powerful ability to exploit latent structure of self-representation...
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09/30/2021
Semi-tensor Product-based TensorDecomposition for Neural Network Compression
The existing tensor networks adopt conventional matrix product for conne...
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05/22/2021
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection
Weakly-supervised anomaly detection aims at learning an anomaly detector...
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04/22/2021
Performance Evaluation of Adversarial Attacks: Discrepancies and Solutions
Recently, adversarial attack methods have been developed to challenge th...
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03/03/2021
Real-World Single Image Super-Resolution: A Brief Review
Single image super-resolution (SISR), which aims to reconstruct a high-r...
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01/20/2021
Scalable Deep Compressive Sensing
Deep learning has been used to image compressive sensing (CS) for enhanc...
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09/15/2020
Decision-based Universal Adversarial Attack
A single perturbation can pose the most natural images to be misclassifi...
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08/26/2020
Siamese Network for RGB-D Salient Object Detection and Beyond
Existing RGB-D salient object detection (SOD) models usually treat RGB a...
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07/26/2020
Deep Embedded Multi-view Clustering with Collaborative Training
Multi-view clustering has attracted increasing attentions recently by ut...
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06/29/2020
Bayesian Low Rank Tensor Ring Model for Image Completion
Low rank tensor ring model is powerful for image completion which recove...
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05/29/2020
Unsupervised Feature Selection via Multi-step Markov Transition Probability
Feature selection is a widely used dimension reduction technique to sele...
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05/28/2020
Improving Generalized Zero-Shot Learning by Semantic Discriminator
It is a recognized fact that the classification accuracy of unseen class...
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05/28/2020
Disentanglement Then Reconstruction: Learning Compact Features for Unsupervised Domain Adaptation
Recent works in domain adaptation always learn domain invariant features...
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05/28/2020
Learning Various Length Dependence by Dual Recurrent Neural Networks
Recurrent neural networks (RNNs) are widely used as a memory model for s...
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05/16/2020
The Power of Triply Complementary Priors for Image Compressive Sensing
Recent works that utilized deep models have achieved superior results in...
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04/22/2020
Hierarchical Tensor Ring Completion
Tensor completion can estimate missing values of a high-order data from ...
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04/21/2020
AMP-Net: Denoising based Deep Unfolding for Compressive Image Sensing
Most compressive sensing (CS) reconstruction methods can be divided into...
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04/21/2020
Frequency-Weighted Robust Tensor Principal Component Analysis
Robust tensor principal component analysis (RTPCA) can separate the low-...
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03/28/2020
Adversarial Imitation Attack
Deep learning models are known to be vulnerable to adversarial examples....
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03/28/2020
DaST: Data-free Substitute Training for Adversarial Attacks
Machine learning models are vulnerable to adversarial examples. For the ...
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01/09/2020
Coupled Tensor Completion via Low-rank Tensor Ring
The coupled tensor decomposition aims to reveal the latent data structur...
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10/14/2019
Distribution-Aware Coordinate Representation for Human Pose Estimation
While being the de facto standard coordinate representation in human pos...
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10/11/2019
Deep Independently Recurrent Neural Network (IndRNN)
Recurrent neural networks (RNNs) are known to be difficult to train due ...
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04/10/2019
C3AE: Exploring the Limits of Compact Model for Age Estimation
Age estimation is a classic learning problem in computer vision. Many la...
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03/31/2019
Robust Tensor Recovery using Low-Rank Tensor Ring
Robust tensor completion recoveries the low-rank and sparse parts from i...
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03/12/2019
Tensor Grid Decomposition with Application to Tensor Completion
The recently prevalent tensor train (TT) and tensor ring (TR) decomposit...
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03/08/2019
Tensor Completion using Balanced Unfolding of Low-Rank Tensor Ring
Tensor completion aims to recover a multi-dimensional array from its inc...
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03/08/2019
Low-Rank Tensor Completion via Tensor Ring with Balanced Unfolding
Tensor completion aims to recover a multi-dimensional array from its inc...
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05/08/2018
Image Ordinal Classification and Understanding: Grid Dropout with Masking Label
Image ordinal classification refers to predicting a discrete target valu...
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05/08/2018
Low Rank Tensor Completion for Multiway Visual Data
Tensor completion recovers missing entries of multiway data. Teh missing...
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03/13/2018
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN
Recurrent neural networks (RNNs) have been widely used for processing se...
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02/08/2018
Hole Filling with Multiple Reference Views in DIBR View Synthesis
Depth-image-based rendering (DIBR) oriented view synthesis has been wide...
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06/16/2017
A Fully Trainable Network with RNN-based Pooling
Pooling is an important component in convolutional neural networks (CNNs...
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03/29/2017
Towards thinner convolutional neural networks through Gradually Global Pruning
Deep network pruning is an effective method to reduce the storage and co...
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02/09/2017
Attribute-controlled face photo synthesis from simple line drawing
Face photo synthesis from simple line drawing is a one-to-many task as s...
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01/15/2017
Iterative Block Tensor Singular Value Thresholding for Extraction of Low Rank Component of Image Data
Tensor principal component analysis (TPCA) is a multi-linear extension o...
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08/15/2016
