
SemiSupervised Video Deraining with Dynamic Rain Generator
While deep learning (DL)based video deraining methods have achieved sig...
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CrossSupervised JointEventExtraction with Heterogeneous Information Networks
Jointeventextraction, which extracts structural information (i.e., ent...
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Variational Image Restoration Network
Deep neural networks (DNNs) have achieved significant success in image r...
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From Rain Removal to Rain Generation
Single image deraining is an important yet challenging issue due to the ...
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Meta Feature Modulator for Longtailed Recognition
Deep neural networks often degrade significantly when training data suff...
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Learning to Purify Noisy Labels via Meta Soft Label Corrector
Recent deep neural networks (DNNs) can easily overfit to biased training...
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MetaLRScheduleNet: Learned LR Schedules that Scale and Generalize
The learning rate (LR) is one of the most important hyperparameters in ...
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ECNUSenseMaker at SemEval2020 Task 4: Leveraging Heterogeneous Knowledge Resources for Commonsense Validation and Explanation
This paper describes our system for SemEval2020 Task 4: Commonsense Val...
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Dual Adversarial Network: Toward Realworld Noise Removal and Noise Generation
Realworld image noise removal is a longstanding yet very challenging t...
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Meta Transition Adaptation for Robust Deep Learning with Noisy Labels
To discover intrinsic interclass transition probabilities underlying da...
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Structural Residual Learning for Single Image Rain Removal
To alleviate the adverse effect of rain streaks in image processing task...
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A Modeldriven Deep Neural Network for Single Image Rain Removal
Deep learning (DL) methods have achieved stateoftheart performance in...
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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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The Asymptotic Distribution of the MLE in Highdimensional Logistic Models: Arbitrary Covariance
We study the distribution of the maximum likelihood estimate (MLE) in hi...
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Neural Networks Weights Quantization: Target Noneretraining Ternary (TNT)
Quantization of weights of deep neural networks (DNN) has proven to be a...
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Understand Dynamic Regret with Switching Cost for Online Decision Making
As a metric to measure the performance of an online method, dynamic regr...
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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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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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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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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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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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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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Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net
Hyperspectral imaging can help better understand the characteristics of ...
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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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Discovering Influential Factors in Variational Autoencoder
In the field of machine learning, it is still a critical issue to identi...
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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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Semisupervised CNN for Single Image Rain Removal
Single image rain removal is a typical inverse problem in computer visio...
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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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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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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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Denoising Hyperspectral Image with Noni.i.d. Noise Structure
Hyperspectral image (HSI) denoising has been attracting much research at...
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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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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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Qian Zhao
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