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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：133/39  |  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  
Face swapping detection based on identity spatial constraints with weighted frequency division 期刊论文
MULTIMEDIA SYSTEMS, 2022, 页码: 14
作者:  Ai, Zupeng;  Peng, Chengwei;  Jiang, Jun;  Li, Zekun;  Li, Bing
收藏  |  浏览/下载：229/0  |  提交时间：2022/11/14
Face swapping  Face manipulation  Frequency division  Identity constraints  
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：319/41  |  提交时间：2022/09/19
Object detection  prediction decoupling  convolutional neural network  
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
Adobe PDF(5681Kb)  |  收藏  |  浏览/下载：404/2  |  提交时间：2022/07/25
Cognition  Video recording  Syntactics  Visualization  Task analysis  Semantics  Linguistics  Visual Commonsense Reasoning  explicit reasoning  syntactic structure  interpretability  
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
Adobe PDF(4827Kb)  |  收藏  |  浏览/下载：262/1  |  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