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COVID-19 Chest CT Image Segmentation – A Deep Convolutional Neural Network Solution
A novel coronavirus disease 2019 (COVID-19) was detected and has spread ...
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Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory
Unsupervised cross-domain person re-identification (Re-ID) aims to adapt...
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Semi-supervised Learning via Conditional Rotation Angle Estimation
Self-supervised learning (SlfSL), aiming at learning feature representat...
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Learning to Zoom-in via Learning to Zoom-out: Real-world Super-resolution by Generating and Adapting Degradation
Most learning-based super-resolution (SR) methods aim to recover high-re...
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Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation
3D point cloud semantic and instance segmentation is crucial and fundame...
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Part-Guided Attention Learning for Vehicle Re-Identification
Vehicle re-identification (Re-ID) often requires one to recognize the fi...
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Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation
Training a semantic segmentation model requires a large amount of pixel-...
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An Effective Two-Branch Model-Based Deep Network for Single Image Deraining
Removing rain effects from an image automatically has many applications ...
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Attention-guided Network for Ghost-free High Dynamic Range Imaging
Ghosting artifacts caused by moving objects or misalignments is a key ch...
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Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection
Deep autoencoder has been extensively used for anomaly detection. Traini...
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Knowledge Adaptation for Efficient Semantic Segmentation
Both accuracy and efficiency are of significant importance to the task o...
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RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion
RGB images differentiate from depth images as they carry more details ab...
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Variational Bayesian Dropout
Variational dropout (VD) is a generalization of Gaussian dropout, which ...
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End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging
Cardiac magnetic resonance (CMR) is used extensively in the diagnosis an...
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MPTV: Matching Pursuit Based Total Variation Minimization for Image Deconvolution
Total variation (TV) regularization has proven effective for a range of ...
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Learning an Optimizer for Image Deconvolution
As an integral component of blind image deblurring, non-blind deconvolut...
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From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur
Removing pixel-wise heterogeneous motion blur is challenging due to the ...
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