CASIA OpenIR

浏览/检索结果: 共23条,第1-10条 帮助

限定条件        
已选(0)清除 条数/页:   排序方式:
Explicit Cross-Modal Representation Learning for Visual Commonsense Reasoning 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 2986-2997
作者:  Zhang, Xi;  Zhang, Feifei;  Xu, Changsheng
收藏  |  浏览/下载:318/0  |  提交时间:2022/07/25
Cognition  Video recording  Syntactics  Visualization  Task analysis  Semantics  Linguistics  Visual Commonsense Reasoning  explicit reasoning  syntactic structure  interpretability  
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:333/64  |  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  
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:198/40  |  提交时间:2022/06/14
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  
Heterogeneous Hierarchical Feature Aggregation Network for Personalized Micro-Video Recommendation 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 805-818
作者:  Cai, Desheng;  Qian, Shengsheng;  Fang, Quan;  Xu, Changsheng
收藏  |  浏览/下载:269/0  |  提交时间:2022/06/06
Graph neural networks  Task analysis  Semantics  Aggregates  Data structures  Collaboration  Visualization  Heterogeneous graph  micro-video recommendation  multi-modal  
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:146/0  |  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  
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:250/0  |  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:312/62  |  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: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:282/0  |  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)