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GCAN: Graph Convolutional Adversarial Network for Unsupervised Domain Adaptation 会议论文
IEEE Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA, JUN 16-20, 2019
作者:  Ma, Xinhong;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(7239Kb)  |  收藏  |  浏览/下载：199/41  |  提交时间：2022/06/14
Margin-Based Adversarial Joint Alignment Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 卷号: 32, 期号: 4, 页码: 2057-2067
作者:  Zuo, Yukun;  Yao, Hantao;  Zhuang, Liansheng;  Xu, Changsheng
收藏  |  浏览/下载：270/0  |  提交时间：2022/06/10
Feature extraction  Adaptation models  Image reconstruction  Generative adversarial networks  Semisupervised learning  Data models  Training  Domain adaptation  joint alignment module  margin-based generative module  
Towards Corruption-Agnostic Robust Domain Adaptation 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2022, 卷号: 18, 期号: 4, 页码: 16
作者:  Xu, Yifan;  Sheng, Kekai;  Dong, Weiming;  Wu, Baoyuan;  Xu, Changsheng;  Hu, Bao-Gang
Adobe PDF(2116Kb)  |  收藏  |  浏览/下载：415/88  |  提交时间：2022/06/10
Domain adaptation  corruption robustness  transfer learning  
Joint Expression Synthesis and Representation Learning for Facial Expression Recognition 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 卷号: 32, 期号: 3, 页码: 1681-1695
作者:  Zhang, Xi;  Zhang, Feifei;  Xu, Changsheng
收藏  |  浏览/下载：221/0  |  提交时间：2022/06/06
Face recognition  Task analysis  Generative adversarial networks  Image synthesis  Image recognition  Faces  Training  Facial expression recognition  facial image synthesis  generative adversarial network  representation learning  
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：323/45  |  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  
Incremental Concept Learning via Online Generative Memory Recall 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 7, 页码: 3206-3216
作者:  Li, Huaiyu;  Dong, Weiming;  Hu, Bao-Gang
收藏  |  浏览/下载：283/0  |  提交时间：2021/08/15
Task analysis  Learning systems  Neural networks  Feature extraction  Visualization  Knowledge engineering  Training  Catastrophic forgetting  continual learning  generative adversarial networks (GANs)  
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：282/39  |  提交时间：2021/03/08
Person re-identification  representation learning  graph convolutional network  
Multi-Level Correlation Adversarial Hashing for Cross-Modal Retrieval 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2020, 卷号: 22, 期号: 12, 页码: 3101-3114
作者:  Ma, Xinhong;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(4322Kb)  |  收藏  |  浏览/下载：293/53  |  提交时间：2021/03/01
Semantics  Correlation  Aircraft propulsion  Deep learning  Bridges  Aircraft  Task analysis  Cross-modal retrieval  adversarial hashing  multi-level correlation  
Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation 期刊论文
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2020, 卷号: 11, 期号: 4, 页码: 20
作者:  Zhang, Yingying;  Fang, Quan;  Qian, Shengsheng;  Xu, Changsheng
Adobe PDF(1626Kb)  |  收藏  |  浏览/下载：314/56  |  提交时间：2021/01/06
Dialogue system  co-attention  adversarial learning  external knowledge  
Deep Multi-Modality Adversarial Networks for Unsupervised Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 卷号: 21, 期号: 9, 页码: 2419-2431
作者:  Ma, Xinhong;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(2142Kb)  |  收藏  |  浏览/下载：339/42  |  提交时间：2019/12/16
Unsupervised domain adaptation  triplet loss  stacked attention  multi-modality  social event recognition