research
∙
04/18/2023
Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes
Multi-frame depth estimation generally achieves high accuracy relying on...
share
research
∙
09/01/2022
The Neural Process Family: Survey, Applications and Perspectives
The standard approaches to neural network implementation yield powerful ...
research
∙
05/25/2022
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
This paper reviews the challenge on constrained high dynamic range (HDR)...
research
∙
02/21/2022
Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning
Continual Learning (CL) methods aim to enable machine learning models to...
research
∙
04/23/2020
COVID-19 Chest CT Image Segmentation – A Deep Convolutional Neural Network Solution
A novel coronavirus disease 2019 (COVID-19) was detected and has spread ...
research
∙
01/13/2020
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...
research
∙
01/09/2020
Semi-supervised Learning via Conditional Rotation Angle Estimation
Self-supervised learning (SlfSL), aiming at learning feature representat...
research
∙
01/08/2020
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...
research
∙
01/06/2020
Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation
3D point cloud semantic and instance segmentation is crucial and fundame...
research
∙
09/13/2019
Part-Guided Attention Learning for Vehicle Re-Identification
Vehicle re-identification (Re-ID) often requires one to recognize the fi...
research
∙
07/29/2019
Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation
Training a semantic segmentation model requires a large amount of pixel-...
research
∙
05/14/2019
An Effective Two-Branch Model-Based Deep Network for Single Image Deraining
Removing rain effects from an image automatically has many applications ...
research
∙
04/23/2019
Attention-guided Network for Ghost-free High Dynamic Range Imaging
Ghosting artifacts caused by moving objects or misalignments is a key ch...
research
∙
04/04/2019
Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection
Deep autoencoder has been extensively used for anomaly detection. Traini...
research
∙
03/12/2019
Knowledge Adaptation for Efficient Semantic Segmentation
Both accuracy and efficiency are of significant importance to the task o...
research
∙
03/02/2019
RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion
RGB images differentiate from depth images as they carry more details ab...
research
∙
11/19/2018
Variational Bayesian Dropout
Variational dropout (VD) is a generalization of Gaussian dropout, which ...
research
∙
10/23/2018
End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging
Cardiac magnetic resonance (CMR) is used extensively in the diagnosis an...
research
∙
10/12/2018
MPTV: Matching Pursuit Based Total Variation Minimization for Image Deconvolution
Total variation (TV) regularization has proven effective for a range of ...
research
∙
04/10/2018
Learning an Optimizer for Image Deconvolution
As an integral component of blind image deblurring, non-blind deconvolut...
research
∙
12/08/2016
