27 citations · 88 across the 13 of their papers we have counts for
13 papers
Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing
Zhihong Chen, Taiping Yao, Kekai Sheng +5
Face anti-spoofing approach based on domain generalization(DG) has drawn growing attention due to its robustness forunseen scenarios. Existing DG methods assume that the do-main la…
DCANet: Dense Context-Aware Network for Semantic Segmentation
Yifu Liu, Chenfeng Xu, Xinyu Jin
As the superiority of context information gradually manifests in advanced semantic segmentation, learning to capture the compact context relationship can help to understand the com…
Synthesizing MR Image Contrast Enhancement Using 3D High-resolution ConvNets
Chao Chen, Catalina Raymond, Bill Speier +5
\textit{Objective:} Gadolinium-based contrast agents (GBCAs) have been widely used to better visualize disease in brain magnetic resonance imaging (MRI). However, gadolinium deposi…
Attention-Guided Discriminative Region Localization and Label Distribution Learning for Bone Age Assessment
Chao Chen, Zhihong Chen, Xinyu Jin +3
Bone age assessment (BAA) is clinically important as it can be used to diagnose endocrine and metabolic disorders during child development. Existing deep learning based methods for…
1D Probabilistic Undersampling Pattern Optimization for MR Image Reconstruction
Shengke Xue, Ruiliang Bai, Xinyu Jin
Magnetic resonance imaging (MRI) is mainly limited by long scanning time and vulnerable to human tissue motion artifacts, in 3D clinical scenarios. Thus, k-space undersampling is u…
HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation
Chao Chen, Zhihang Fu, Zhihong Chen +4
Minimizing the discrepancy of feature distributions between different domains is one of the most promising directions in unsupervised domain adaptation. From the perspective of dis…
Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation
Zhihong Chen, Chao Chen, Zhaowei Cheng +3
One crucial aspect of partial domain adaptation (PDA) is how to select the relevant source samples in the shared classes for knowledge transfer. Previous PDA methods tackle this pr…
Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation
Chao Chen, Zhihang Fu, Zhihong Chen +3
Recent advances in unsupervised domain adaptation mainly focus on learning shared representations by global distribution alignment without considering class information across doma…
Truncated nuclear norm regularization for low-rank tensor completion
Shengke Xue, Wenyuan Qiu, Fan Liu +1
Recently, low-rank tensor completion has become increasingly attractive in recovering incomplete visual data. Considering a color image or video as a three-dimensional (3D) tensor,…
Double Weighted Truncated Nuclear Norm Regularization for Low-Rank Matrix Completion
Shengke Xue, Wenyuan Qiu, Fan Liu +1
Matrix completion focuses on recovering a matrix from a small subset of its observed elements, and has already gained cumulative attention in computer vision. Many previous approac…
Parameter Transfer Extreme Learning Machine based on Projective Model
Chao Chen, Boyuan Jiang, Xinyu Jin
Recent years, transfer learning has attracted much attention in the community of machine learning. In this paper, we mainly focus on the tasks of parameter transfer under the frame…
Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation
Chao Chen, Zhihong Chen, Boyuan Jiang +1
Recently, considerable effort has been devoted to deep domain adaptation in computer vision and machine learning communities. However, most of existing work only concentrates on le…
Low-Rank Tensor Completion by Truncated Nuclear Norm Regularization
Shengke Xue, Wenyuan Qiu, Fan Liu +1
Currently, low-rank tensor completion has gained cumulative attention in recovering incomplete visual data whose partial elements are missing. By taking a color image or video as a…