CASIA OpenIR

浏览/检索结果: 共15条,第1-10条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
Learning Domain Invariant Representations for Generalizable Person Re-Identification 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 509-523
作者:  Zhang, Yi-Fan;  Zhang, Zhang;  Li, Da;  Jia, Zhen;  Wang, Liang;  Tan, Tieniu
收藏  |  浏览/下载:204/0  |  提交时间:2023/03/20
Generalizable person re-Identification  disentanglement  backdoor adjustment  
Mask-guided contrastive attention and two-stream metric co-learning for person Re-identification 期刊论文
NEUROCOMPUTING, 2021, 卷号: 465, 页码: 561-573
作者:  Song, Chunfeng;  Shan, Caifeng;  Huang, Yan;  Wang, Liang
收藏  |  浏览/下载:215/0  |  提交时间:2021/11/03
Person ReID  Contrastive attention model  Two-stream metric learning  
FA-GAN: Face Augmentation GAN for Deformation-Invariant Face Recognition 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2021, 卷号: 16, 期号: 0, 页码: 2341-2355
作者:  Luo, Mandi;  Cao, Jie;  Ma, Xin;  Zhang, Xiaoyu;  He, Ran
Adobe PDF(4742Kb)  |  收藏  |  浏览/下载:328/55  |  提交时间:2021/04/21
Face recognition  Strain  Geometry  Frequency division multiplexing  Training  Task analysis  Semantics  Face augmentation  deformation-invariant face recognition  face disentanglement  graph convolutional networks  
Partial NIR-VIS Heterogeneous Face Recognition With Automatic Saliency Search 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2021, 卷号: 16, 页码: 5003-5017
作者:  Luo, Mandi;  Ma, Xin;  Li, Zhihang;  Cao, Jie;  He, Ran
Adobe PDF(4346Kb)  |  收藏  |  浏览/下载:265/55  |  提交时间:2021/12/28
Face recognition  Task analysis  Visualization  Image recognition  Lighting  Feature extraction  Training  Heterogeneous face recognition  near infrared-visible matching  information bottleneck  neural architecture search  
Learning Aligned Image-Text Representations Using Graph Attentive Relational Network 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 期号: 30, 页码: 1840-1852
作者:  Jing, Ya;  Wang, Wei;  Wang, Liang;  Tan, Tieniu
Adobe PDF(4532Kb)  |  收藏  |  浏览/下载:316/51  |  提交时间:2021/03/08
Graph neural networks  Visualization  Semantics  Task analysis  Feature extraction  Annotations  Recurrent neural networks  Image-text matching  cross-modal retrieval  person search  graph neural network  
Learning Coarse-to-Fine Graph Neural Networks for Video-Text Retrieval 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 2386-2397
作者:  Wang, Wei;  Gao, Junyu;  Yang, Xiaoshan;  Xu, Changsheng
Adobe PDF(2165Kb)  |  收藏  |  浏览/下载:319/44  |  提交时间:2021/11/02
Feature extraction  Encoding  Task analysis  Semantics  Data models  Cognition  Focusing  Video-text retrieval  graph neural network  coarse-to-fine strategy  
Joint Person Objectness and Repulsion for Person Search 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 685-696
作者:  Yao, Hantao;  Xu, Changsheng
收藏  |  浏览/下载:182/0  |  提交时间:2021/03/02
Probes  Search problems  Detectors  Proposals  Visualization  Noise measurement  Transforms  Detection-Matching person search  person repulsion  person objectness  person re-identification  
Part-based Structured Representation Learning for Person Re-identification 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 卷号: 16, 期号: 4, 页码: 22
作者:  Li, Yaoyu;  Yao, Hantao;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(19052Kb)  |  收藏  |  浏览/下载:273/36  |  提交时间:2021/03/08
Person re-identification  representation learning  graph convolutional network  
ScleraSegNet: an Improved U-Net Model with Attention for Accurate Sclera Segmentation 会议论文
, Crete, Greece, 4-7 June 2019
作者:  Wang Caiyong;  He Yong;  Liu Yunfan;  He Zhaofeng;  He Ran;  Sun Zhenan
浏览  |  Adobe PDF(313Kb)  |  收藏  |  浏览/下载:319/72  |  提交时间:2020/06/10
Improve Person Re-Identification With Part Awareness Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7468-7481
作者:  Huang, Houjing;  Yang, Wenjie;  Lin, Jinbin;  Huang, Guan;  Xu, Jiamiao;  Wang, Guoli;  Chen, Xiaotang;  Huang, Kaiqi
Adobe PDF(3927Kb)  |  收藏  |  浏览/下载:310/55  |  提交时间:2020/08/31
Person re-identification  part awareness  part segmentation  multi-task learning