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CASIA OpenIR
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Feature Disentanglement Network: Multi-Object Tracking Needs More Differentiated Features 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2024, 卷号: 20, 期号: 3, 页码: 22
作者:  Guo, Wen;  Quan, Wuzhou;  Gao, Junyu;  Zhang, Tianzhu;  Xu, Changsheng
收藏  |  浏览/下载：78/0  |  提交时间：2024/03/26
Multiple object tracking  Feature disentanglement network  one-shot tracking  feature enhancement  
Uncertainty-Aware Dual-Evidential 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: 12, 页码: 15896-15911
作者:  Chen, Mengyuan;  Gao, Junyu;  Xu, Changsheng
收藏  |  浏览/下载：57/0  |  提交时间：2024/03/26
Uncertainty  Background noise  Task analysis  Location awareness  Measurement uncertainty  Interference  Predictive models  Weakly-supervised temporal action localization  evidential deep learning  uncertainty estimation  
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：117/0  |  提交时间：2023/11/16
Weakly-supervised  video  action localization  semantic  temporal context  correlation learning  
Learning Hierarchical Video Graph Networks for One-Stop Video Delivery 期刊论文
ACM Transactions on Multimedia Computing, Communications, and Applications, 2022, 卷号: 18, 期号: 1, 页码: 1-23
作者:  Song, Yaguang;  Gao, Junyu;  Yang, Xiaoshan;  Xu, Changsheng
Adobe PDF(7608Kb)  |  收藏  |  浏览/下载：183/57  |  提交时间：2023/04/25
Cross modal  video retrieval  deep learning  graph neural networks  
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：382/75  |  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  
The Model May Fit You: User-Generalized Cross-Modal Retrieval 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 24, 页码: 2998-3012
作者:  Ma, Xinhong;  Yang, Xiaoshan;  Gao, Junyu;  Xu, Changsheng
Adobe PDF(6549Kb)  |  收藏  |  浏览/下载：289/56  |  提交时间：2022/06/17
cross-modal retrieval  domain generalization  meta-learning  
Learning Dual-Pooling Graph Neural Networks for Few-Shot Video Classification 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 4285-4296
作者:  Hu, Yufan;  Gao, Junyu;  Xu, Changsheng
收藏  |  浏览/下载：177/0  |  提交时间：2021/12/28
Task analysis  Feature extraction  Training  Testing  Streaming media  Data models  Semantics  Few-shot learning  graph neural networks  video classification  
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：350/69  |  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：356/47  |  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  
Health Status Prediction with Local-Global Heterogeneous Behavior Graph 期刊论文
ACM Transactions on Multimedia Computing Communications and Applications, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Ma, Xuan;  Yang, Xiaoshan;  Gao, Junyu;  Xu, Changsheng
Adobe PDF(1170Kb)  |  收藏  |  浏览/下载：270/75  |  提交时间：2021/06/16
Health Status Prediction  Graph Neural Networks  Individual Behavior