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Dual Instance-Consistent Network for Cross-Domain Object Detection 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 6, 页码: 7338-7352
作者:  Jiao, Yifan;  Yao, Hantao;  Xu, Changsheng
收藏  |  浏览/下载：40/0  |  提交时间：2023/11/17
Feature extraction  Object detection  Detectors  Visualization  Proposals  Head  Task analysis  Cross-domain object detection  domain-specific description  dual instance-consistent network  
Semantic and Temporal Contextual Correlation Learning for Weakly-Supervised Temporal Action Localization 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 10, 页码: 12427-12443
作者:  Fu, Jie;  Gao, Junyu;  Xu, Changsheng
收藏  |  浏览/下载：82/0  |  提交时间：2023/11/16
Weakly-supervised  video  action localization  semantic  temporal context  correlation learning  
Weakly-Supervised Video Object Grounding Via Learning Uni-Modal Associations 期刊论文
IEEE Transactions on Multimedia, 2022, 卷号: 25, 页码: 1-12
作者:  Wang, Wei;  Gao, Junyu;  Xu, Changsheng
Adobe PDF(5406Kb)  |  收藏  |  浏览/下载：109/32  |  提交时间：2023/04/25
Visualization  Grounding  Task analysis  Prototypes  Annotations  Uncertainty  Proposals  Cross-modal retrieval  weakly-supervised learning  video object grounding  uni-modal association  
PDNet: Toward Better One-Stage Object Detection With Prediction Decoupling 期刊论文
IEEE Transactions on Image Processing, 2022, 卷号: 31, 页码: 5121-5133
作者:  Yang, Li;  Xu, Yan;  Wang, Shaoru;  Yuan, Chunfeng;  Zhang, Ziqi;  Li, Bing;  Hu, Weiming
Adobe PDF(3190Kb)  |  收藏  |  浏览/下载：257/35  |  提交时间：2022/09/19
Object detection  prediction decoupling  convolutional neural network  
Holographic Feature Learning of Egocentric-Exocentric Videos for Multi-Domain Action Recognition 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 2273-2286
作者:  Huang, Yi;  Yang, Xiaoshan;  Gao, Junyun;  Xu, Changsheng
Adobe PDF(2409Kb)  |  收藏  |  浏览/下载：340/65  |  提交时间：2022/07/25
Videos  Feature extraction  Visualization  Task analysis  Computational modeling  Target recognition  Prototypes  Egocentric videos  exocentric videos  holographic feature  multi-domain  action recognition  
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：226/0  |  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  
A unified framework for multi-modal federated learning 期刊论文
NEUROCOMPUTING, 2022, 卷号: 480, 页码: 110-118
作者:  Xiong, Baochen;  Yang, Xiaoshan;  Qi, Fan;  Xu, Changsheng
收藏  |  浏览/下载：251/0  |  提交时间：2022/06/06
Multi-modal  Federated learning  Co-attention  
Learning to Model Relationships for Zero-Shot Video Classification 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 卷号: 43, 期号: 10, 页码: 3476-3491
作者:  Gao, Junyu;  Zhang, Tianzhu;  Xu, Changsheng
收藏  |  浏览/下载：256/0  |  提交时间：2021/11/04
Zero-shot video classification  graph neural networks  zero-shot learning  deep attention model  
Unsupervised Video Summarization via Relation-Aware Assignment Learning 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 3203-3214
作者:  Gao, Junyu;  Yang, Xiaoshan;  Zhang, Yingying;  Xu, Changsheng
Adobe PDF(3649Kb)  |  收藏  |  浏览/下载：318/62  |  提交时间：2021/11/03
Feature extraction  Training  Optimization  Semantics  Recurrent neural networks  Task analysis  Graph neural network  unsupervised learning  video summarization  
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：330/45  |  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