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Geometry Sensitive Cross-Modal Reasoning for Composed Query Based Image Retrieval 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 1000-1011
作者:  Zhang, Feifei;  Xu, Mingliang;  Xu, Changsheng
收藏  |  浏览/下载：228/0  |  提交时间：2022/02/16
Visualization  Image retrieval  Semantics  Cognition  Geometry  Task analysis  Electronic mail  Composed query based image retrieval  semantic gap  spatial structure  inter-modal attention  text-guided visual reasoning  
Attention-Based Multi-Source Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 3793-3803
作者:  Zuo, Yukun;  Yao, Hantao;  Xu, Changsheng
收藏  |  浏览/下载：237/0  |  提交时间：2021/05/06
Correlation  Adaptation models  Feature extraction  Target recognition  Data models  Transfer learning  Visualization  Multi-source domain adaptation  attention-based multi-source domain adaptation  weighted moment distance  
SAN: Selective Alignment Network for Cross-Domain Pedestrian Detection 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 2155-2167
作者:  Jiao, Yifan;  Yao, Hantao;  Xu, Changsheng
收藏  |  浏览/下载：240/0  |  提交时间：2021/03/15
Proposals  Feature extraction  Detectors  Visualization  Training  Image color analysis  Adaptation models  Cross-domain pedestrian detection  instance-level adaptation network  image-level adaptation network  pedestrian detection  
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：176/0  |  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  
SMART: Joint Sampling and Regression for Visual Tracking 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 8, 页码: 3923-3935
作者:  Gao, Junyu;  Zhang, Tianzhu;  Xu, Changsheng
浏览  |  Adobe PDF(9244Kb)  |  收藏  |  浏览/下载：327/40  |  提交时间：2019/09/30
Visual tracking  deep learning  sampling and regression