
Feature Encoding with AutoEncoders for Weaklysupervised Anomaly Detection
Weaklysupervised anomaly detection aims at learning an anomaly detector...
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Performance Evaluation of Adversarial Attacks: Discrepancies and Solutions
Recently, adversarial attack methods have been developed to challenge th...
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RealWorld Single Image SuperResolution: A Brief Review
Single image superresolution (SISR), which aims to reconstruct a highr...
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Scalable Deep Compressive Sensing
Deep learning has been used to image compressive sensing (CS) for enhanc...
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Decisionbased Universal Adversarial Attack
A single perturbation can pose the most natural images to be misclassifi...
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Siamese Network for RGBD Salient Object Detection and Beyond
Existing RGBD salient object detection (SOD) models usually treat RGB a...
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Deep Embedded Multiview Clustering with Collaborative Training
Multiview clustering has attracted increasing attentions recently by ut...
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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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Unsupervised Feature Selection via Multistep Markov Transition Probability
Feature selection is a widely used dimension reduction technique to sele...
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Improving Generalized ZeroShot Learning by Semantic Discriminator
It is a recognized fact that the classification accuracy of unseen class...
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Disentanglement Then Reconstruction: Learning Compact Features for Unsupervised Domain Adaptation
Recent works in domain adaptation always learn domain invariant features...
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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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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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Hierarchical Tensor Ring Completion
Tensor completion can estimate missing values of a highorder data from ...
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AMPNet: Denoising based Deep Unfolding for Compressive Image Sensing
Most compressive sensing (CS) reconstruction methods can be divided into...
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FrequencyWeighted Robust Tensor Principal Component Analysis
Robust tensor principal component analysis (RTPCA) can separate the low...
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Adversarial Imitation Attack
Deep learning models are known to be vulnerable to adversarial examples....
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DaST: Datafree Substitute Training for Adversarial Attacks
Machine learning models are vulnerable to adversarial examples. For the ...
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Coupled Tensor Completion via Lowrank Tensor Ring
The coupled tensor decomposition aims to reveal the latent data structur...
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DistributionAware Coordinate Representation for Human Pose Estimation
While being the de facto standard coordinate representation in human pos...
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Deep Independently Recurrent Neural Network (IndRNN)
Recurrent neural networks (RNNs) are known to be difficult to train due ...
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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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Robust Tensor Recovery using LowRank Tensor Ring
Robust tensor completion recoveries the lowrank and sparse parts from i...
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Tensor Grid Decomposition with Application to Tensor Completion
The recently prevalent tensor train (TT) and tensor ring (TR) decomposit...
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Tensor Completion using Balanced Unfolding of LowRank Tensor Ring
Tensor completion aims to recover a multidimensional array from its inc...
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LowRank Tensor Completion via Tensor Ring with Balanced Unfolding
Tensor completion aims to recover a multidimensional array from its inc...
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Image Ordinal Classification and Understanding: Grid Dropout with Masking Label
Image ordinal classification refers to predicting a discrete target valu...
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Low Rank Tensor Completion for Multiway Visual Data
Tensor completion recovers missing entries of multiway data. Teh missing...
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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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Hole Filling with Multiple Reference Views in DIBR View Synthesis
Depthimagebased rendering (DIBR) oriented view synthesis has been wide...
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A Fully Trainable Network with RNNbased Pooling
Pooling is an important component in convolutional neural networks (CNNs...
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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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Attributecontrolled face photo synthesis from simple line drawing
Face photo synthesis from simple line drawing is a onetomany task as s...
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Iterative Block Tensor Singular Value Thresholding for Extraction of Low Rank Component of Image Data
Tensor principal component analysis (TPCA) is a multilinear extension o...
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Every Filter Extracts A Specific Texture In Convolutional Neural Networks
Many works have concentrated on visualizing and understanding the inner ...
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