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Margin-Based Adversarial Joint Alignment Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 卷号: 32, 期号: 4, 页码: 2057-2067
作者:  Zuo, Yukun;  Yao, Hantao;  Zhuang, Liansheng;  Xu, Changsheng
收藏  |  浏览/下载：294/0  |  提交时间：2022/06/10
Feature extraction  Adaptation models  Image reconstruction  Generative adversarial networks  Semisupervised learning  Data models  Training  Domain adaptation  joint alignment module  margin-based generative module  
Tell, Imagine, and Search: End-to-end Learning for Composing Text and Image to Image Retrieval 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2022, 卷号: 18, 期号: 2, 页码: 23
作者:  Zhang, Feifei;  Xu, Mingliang;  Xu, Changsheng
收藏  |  浏览/下载：228/0  |  提交时间：2022/06/10
Composing text and image to image retrieval  end-to-end  image generation  generative adversarial network  global-local  
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
收藏  |  浏览/下载：244/0  |  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  
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：348/46  |  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  
SSAP: Single-Shot Instance Segmentation With Affinity Pyramid 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2021, 卷号: 31, 期号: 2, 页码: 661-673
作者:  Gao, Naiyu;  Shan, Yanhu;  Wang, Yupei;  Zhao, Xin;  Huang, Kaiqi
Adobe PDF(4190Kb)  |  收藏  |  浏览/下载：314/52  |  提交时间：2021/03/29
Instance segmentation  panoptic segmentation  pixel-pair affinity  graph partition  
Learning Aligned Image-Text Representations Using Graph Attentive Relational Network 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 期号: 30, 页码: 1840-1852
作者:  Jing, Ya;  Wang, Wei;  Wang, Liang;  Tan, Tieniu
Adobe PDF(4532Kb)  |  收藏  |  浏览/下载：352/58  |  提交时间：2021/03/08
Graph neural networks  Visualization  Semantics  Task analysis  Feature extraction  Annotations  Recurrent neural networks  Image-text matching  cross-modal retrieval  person search  graph neural network  
Part-based Structured Representation Learning for Person Re-identification 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 卷号: 16, 期号: 4, 页码: 22
作者:  Li, Yaoyu;  Yao, Hantao;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(19052Kb)  |  收藏  |  浏览/下载：310/46  |  提交时间：2021/03/08
Person re-identification  representation learning  graph convolutional network  
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：340/65  |  提交时间：2020/08/31
Person re-identification  part awareness  part segmentation  multi-task learning  
Re-ranking Image-text Matching by Adaptive Metric Fusion 期刊论文
PATTERN RECOGNITION, 2020, 卷号: 104, 期号: 1, 页码: 13
作者:  Niu, Kai;  Huang, Yan;  Wang, Liang
浏览  |  Adobe PDF(2236Kb)  |  收藏  |  浏览/下载：489/112  |  提交时间：2020/06/22
Image-text matching  Re-ranking method  Adaptive metric fusion  
Frame-GAN: Increasing the frame rate of gait videos with generative adversarial networks 期刊论文
NEUROCOMPUTING, 2020, 卷号: 380, 页码: 95-104
作者:  Xue, Wei;  Ai, Hong;  Sun, Tianyu;  Song, Chunfeng;  Huang, Yan;  Wang, Liang
收藏  |  浏览/下载：302/0  |  提交时间：2020/03/30
Gait recognition  Generative adversarial networks  Metric learning  Deep learning