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CASIA OpenIR
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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：8/0  |  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  
Understanding and Mitigating Overfitting in Prompt Tuning for Vision-Language Models 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 9, 页码: 4616-4629
作者:  Ma, Chengcheng;  Liu, Yang;  Deng, Jiankang;  Xie, Lingxi;  Dong, Weiming;  Xu, Changsheng
Adobe PDF(1644Kb)  |  收藏  |  浏览/下载：95/12  |  提交时间：2023/11/16
Vision-language model  prompt tuning  over-fitting  subspace learning  gradient projection  
Emotion-Aware Music Driven Movie Montage 期刊论文
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2023, 卷号: 38, 期号: 3, 页码: 540-553
作者:  Liu, Wu-Qin;  Lin, Min-Xuan;  Huang, Hai-Bin;  Ma, Chong-Yang;  Song, Yu;  Dong, Wei-Ming;  Xu, Chang-Sheng
收藏  |  浏览/下载：96/0  |  提交时间：2023/12/21
movie montage  emotion analysis  audio-visual modality  contrastive learning  
Recovering Generalization via Pre-training-like Knowledge Distillation for Out-of-Distribution Visual Question Answering 期刊论文
IEEE Transactions on Multimedia, 2023, 页码: 1-15
作者:  Song, Yaguang;  Yang, Xiaoshan;  Wang, Yaowei;  Xu, Changsheng
Adobe PDF(2397Kb)  |  收藏  |  浏览/下载：160/43  |  提交时间：2023/06/12
Multi-modal Foundation Model  Out-of-Distribution Generalization  Visual Question Answering  Knowledge Distillation  
Self-supervised Calorie-aware Heterogeneous Graph Networks for Food Recommendation 期刊论文
ACM Transactions on Multimedia Computing, Communications, and Applications, 2023, 卷号: 19, 期号: 1s, 页码: 1-23
作者:  Song, Yaguang;  Yang, Xiaoshan;  Xu, Changsheng
Adobe PDF(1381Kb)  |  收藏  |  浏览/下载：165/54  |  提交时间：2023/06/12
Food recommendation  recipe calories  heterogeneous graph  selfsupervised learning  
Dual Structural Knowledge Interaction for Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 卷号: 25, 页码: 9057-9070
作者:  Zuo, Yukun;  Yao, Hantao;  Zhuang, Liansheng;  Xu, Changsheng
收藏  |  浏览/下载：14/0  |  提交时间：2024/02/21
Manifolds  Feature extraction  Adaptation models  Representation learning  Task analysis  Semisupervised learning  Pattern recognition  Domain adaptation  structural knowledge  dual structural knowledge interaction  
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：390/83  |  提交时间：2022/06/10
Domain adaptation  corruption robustness  transfer learning  
Learning Semantic-Aware Spatial-Temporal Attention for Interpretable Action Recognition 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 卷号: 32, 期号: 8, 页码: 5213-5224
作者:  Fu, Jie;  Gao, Junyu;  Xu, Changsheng
收藏  |  浏览/下载：265/0  |  提交时间：2022/09/19
Visualization  Semantics  Task analysis  Three-dimensional displays  Feature extraction  Solid modeling  Predictive models  Semantic-aware  spatial-temporal attention  interpretable  action recognition  
Learning to Learn a Cold-start Sequential Recommender 期刊论文
ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2022, 卷号: 40, 期号: 2, 页码: 25
作者:  Huang, Xiaowen;  Sang, Jitao;  Yu, Jian;  Xu, Changsheng
收藏  |  浏览/下载：200/0  |  提交时间：2022/06/06
Cold-start recommendation  meta-learning  graph representation  sequential recommendation  
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：133/41  |  提交时间：2023/04/25
Cross modal  video retrieval  deep learning  graph neural networks