
Video Rain/Snow Removal by Transformed Online Multiscale Convolutional Sparse Coding
Video rain/snow removal from surveillance videos is an important task in...
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Progressive Image Deraining Networks: A Better and Simpler Baseline
Along with the deraining performance improvement of deep networks, their...
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Discriminative Feature Learning with Foreground Attention for Person ReIdentification
The performance of person reidentification (ReID) seriously depends on...
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Small Sample Learning in Big Data Era
As a promising area in artificial intelligence, a new learning paradigm,...
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Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net
Hyperspectral imaging can help better understand the characteristics of ...
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Variational Denoising Network: Toward Blind Noise Modeling and Removal
Blind image denoising is an important yet very challenging problem in co...
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A Survey on Rain Removal from Video and Single Image
Rain streaks might severely degenerate the performance of video/image pr...
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Simplex Representation for Subspace Clustering
Spectral clustering based methods have achieved leading performance on s...
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Semisupervised CNN for Single Image Rain Removal
Single image rain removal is a typical inverse problem in computer visio...
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Deep SelfPaced Learning for Person ReIdentification
Person reidentification (ReID) usually suffers from noisy samples with...
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On Convergence Property of Implicit Selfpaced Objective
Selfpaced learning (SPL) is a new methodology that simulates the learni...
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Hyperspectral Image Restoration via Total Variation Regularized Lowrank Tensor Decomposition
Hyperspectral images (HSIs) are often corrupted by a mixture of several ...
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Fewshot Object Detection
In this paper, we study object detection using a large pool of unlabeled...
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SPLBoost: An Improved Robust Boosting Algorithm Based on Selfpaced Learning
It is known that Boosting can be interpreted as a gradient descent techn...
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Robust Online Matrix Factorization for Dynamic Background Subtraction
We propose an effective online background subtraction method, which can ...
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A General Model for Robust Tensor Factorization with Unknown Noise
Because of the limitations of matrix factorization, such as losing spati...
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Bridging Saliency Detection to Weakly Supervised Object Detection Based on Selfpaced Curriculum Learning
Weaklysupervised object detection (WOD) is a challenging problems in co...
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Denoising Hyperspectral Image with Noni.i.d. Noise Structure
Hyperspectral image (HSI) denoising has been attracting much research at...
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Active SelfPaced Learning for CostEffective and Progressive Face Identification
This paper aims to develop a novel costeffective framework for face ide...
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Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Discriminative model learning for image denoising has been recently attr...
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Strategies for Searching Video Content with Text Queries or Video Examples
The large number of usergenerated videos uploaded on to the Internet ev...
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A novel learningbased frame pooling method for Event Detection
Detecting complex events in a large video collection crawled from video ...
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Lowrank Matrix Factorization under General Mixture Noise Distributions
Many computer vision problems can be posed as learning a lowdimensional...
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FastMMD: Ensemble of Circular Discrepancy for Efficient TwoSample Test
The maximum mean discrepancy (MMD) is a recently proposed test statistic...
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Detailpreserving and Contentaware Variational Multiview Stereo Reconstruction
Accurate recovery of 3D geometrical surfaces from calibrated 2D multivi...
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Total Variation Regularized Tensor RPCA for Background Subtraction from Compressive Measurements
Background subtraction has been a fundamental and widely studied task in...
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Iterated Support Vector Machines for Distance Metric Learning
Distance metric learning aims to learn from the given training data a va...
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DensityBased Region Search with Arbitrary Shape for Object Localization
Region search is widely used for object localization. Typically, the reg...
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On the Optimal Solution of Weighted Nuclear Norm Minimization
In recent years, the nuclear norm minimization (NNM) problem has been at...
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A recursive divideandconquer approach for sparse principal component analysis
In this paper, a new method is proposed for sparse PCA based on the recu...
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DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation
In realworld crowd counting applications, the crowd densities vary grea...
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PMGANs: Discriminative Representation Learning for Action Recognition Using Partialmodalities
Data of different modalities generally convey complimentary but heteroge...
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Understanding SelfPaced Learning under Concave Conjugacy Theory
By simulating the easytohard learning manners of humans/animals, the l...
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Unsupervised/Semisupervised Deep Learning for Lowdose CT Enhancement
Recently, deep learning(DL) methods have been proposed for the lowdose ...
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Discovering Influential Factors in Variational Autoencoder
In the field of machine learning, it is still a critical issue to identi...
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Enhanced 3DTV Regularization and Its Applications on Hyperspectral Image Denoising and Compressed Sensing
The 3D total variation (3DTV) is a powerful regularization term, which ...
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Model Inconsistent but Correlated Noise: Multiview Subspace Learning with Regularized Mixture of Gaussians
Multiview subspace learning (MSL) aims to find a lowdimensional subspa...
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Tug the Student to Learn Right: Progressive Gradient Correcting by Metalearner on Corrupted Labels
While deep networks have strong fitting capability to complex input patt...
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Push the Student to Learn Right: Progressive Gradient Correcting by Metalearner on Corrupted Labels
While deep networks have strong fitting capability to complex input patt...
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Variational Bayes' method for functions with applications to some inverse problems
Bayesian approach as a useful tool for quantifying uncertainties has bee...
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Learning Adaptive Loss for Robust Learning with Noisy Labels
Robust loss minimization is an important strategy for handling robust le...
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LTNet: Label Transfer by Learning Reversible Voxelwise Correspondence for Oneshot Medical Image Segmentation
We introduce a oneshot segmentation method to alleviate the burden of m...
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