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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：282/38  |  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：350/70  |  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  
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：327/64  |  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：336/45  |  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  
FA-GAN: Face Augmentation GAN for Deformation-Invariant Face Recognition 期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2021, 卷号: 16, 期号: 0, 页码: 2341-2355
作者:  Luo, Mandi;  Cao, Jie;  Ma, Xin;  Zhang, Xiaoyu;  He, Ran
Adobe PDF(4742Kb)  |  收藏  |  浏览/下载：356/58  |  提交时间：2021/04/21
Face recognition  Strain  Geometry  Frequency division multiplexing  Training  Task analysis  Semantics  Face augmentation  deformation-invariant face recognition  face disentanglement  graph convolutional networks  
Skeleton-based action recognition with hierarchical spatial reasoning and temporal stack learning network 期刊论文
PATTERN RECOGNITION, 2020, 卷号: 107, 期号: 107511, 页码: 12
作者:  Si, Chenyang;  Jing, Ya;  Wang, Wei;  Wang, Liang;  Tan, Tieniu
Adobe PDF(2378Kb)  |  收藏  |  浏览/下载：368/70  |  提交时间：2020/08/31
Skeleton-based action recognition  Hierarchical spatial reasoning  Temporal stack learning  Clip-based incremental loss  
Improve Person Re-Identification With Part Awareness Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7468-7481
作者:  Huang, Houjing;  Yang, Wenjie;  Lin, Jinbin;  Huang, Guan;  Xu, Jiamiao;  Wang, Guoli;  Chen, Xiaotang;  Huang, Kaiqi
Adobe PDF(3927Kb)  |  收藏  |  浏览/下载：326/59  |  提交时间：2020/08/31
Person re-identification  part awareness  part segmentation  multi-task learning  
Long video question answering: A Matching-guided Attention Model 期刊论文
PATTERN RECOGNITION, 2020, 卷号: 102, 期号: 1, 页码: 11
作者:  Wang, Weining;  Huang, Yan;  Wang, Liang
Adobe PDF(1963Kb)  |  收藏  |  浏览/下载：375/73  |  提交时间：2020/06/02
Long video QA  Matching-guided attention  
Recurrent Prediction with Spatio-temporal Attention for Crowd Attribute Recognition 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2019, 卷号: 30, 期号: Early Access, 页码: 1 - 1
作者:  Li, Qiaozhe;  Zhao, Xin;  He, Ran;  Huang, Kaiqi
浏览  |  Adobe PDF(2648Kb)  |  收藏  |  浏览/下载：402/104  |  提交时间：2020/01/14
Crowd video understanding , Attribute recognition , Attention mechanism , Multi-label classification  
GaitNet: An end-to-end network for gait based human identification 期刊论文
PATTERN RECOGNITION, 2019, 卷号: 96, 期号: 106988, 页码: 11
作者:  Song, Chunfeng;  Huang, Yongzhen;  Huang, Yan;  Jia, Ning;  Wang, Liang
浏览  |  Adobe PDF(3015Kb)  |  收藏  |  浏览/下载：613/163  |  提交时间：2019/12/16
Gait recognition  Video-based human identification  End-to-end CNN  Joint learning