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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：297/48  |  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  
Urban Scene LOD Vectorized Modeling From Photogrammetry Meshes 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 7458-7471
作者:  Han, Jiali;  Zhu, Lingjie;  Gao, Xiang;  Hu, Zhanyi;  Zhou, Liyang;  Liu, Hongmin;  Shen, Shuhan
Adobe PDF(8168Kb)  |  收藏  |  浏览/下载：238/32  |  提交时间：2021/11/03
Urban reconstruction  building modeling  Markov random field  segment based modeling  
An Iterative Co-Training Transductive Framework for Zero Shot Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 6943-6956
作者:  Liu, Bo;  Hu, Lihua;  Dong, Qiulei;  Hu, Zhanyi
Adobe PDF(2452Kb)  |  收藏  |  浏览/下载：224/52  |  提交时间：2021/11/02
Visualization  Semantics  Training  Feature extraction  Testing  Detectors  Predictive models  Zero-shot learning  transductive learning co-training  
Nocal-Siam: Refining Visual Features and Response With Advanced Non-Local Blocks for Real-Time Siamese Tracking 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 2656-2668
作者:  Tan, Huibin;  Zhang, Xiang;  Zhang, Zhipeng;  Lan, Long;  Zhang, Wenju;  Luo, Zhigang
Adobe PDF(2898Kb)  |  收藏  |  浏览/下载：156/37  |  提交时间：2021/03/29
Target tracking  Visualization  Feature extraction  Real-time systems  Oceans  Convolution  Task analysis  Siamese trackers  non-local attention  supervisedly attentive  
Semi-Supervised Scene Text Recognition 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 3005-3016
作者:  Gao, Yunze;  Chen, Yingying;  Wang, Jinqiao;  Lu, Hanqing
收藏  |  浏览/下载：247/0  |  提交时间：2021/04/06
Text recognition  Reinforcement learning  Training  Feature extraction  Annotations  Probability distribution  Predictive models  Semi-supervised scene text recognition  embedding  reinforcement learning  
Extremely Lightweight Skeleton-Based Action Recognition With ShiftGCN plus 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 7333-7348
作者:  Cheng, Ke;  Zhang, Yifan;  He, Xiangyu;  Cheng, Jian;  Lu, Hanqing
Adobe PDF(3205Kb)  |  收藏  |  浏览/下载：232/13  |  提交时间：2021/11/03
Skeleton-based action recognition  graph convolutional network  lightweight network  shift network  
Attention-Based Multi-Source Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 3793-3803
作者:  Zuo, Yukun;  Yao, Hantao;  Xu, Changsheng
收藏  |  浏览/下载：221/0  |  提交时间：2021/05/06
Correlation  Adaptation models  Feature extraction  Target recognition  Data models  Transfer learning  Visualization  Multi-source domain adaptation  attention-based multi-source domain adaptation  weighted moment distance  
Learning Category- and Instance-Aware Pixel Embedding for Fast Panoptic Segmentation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 期号: 0, 页码: 6013
作者:  Gao, Naiyu;  Shan, Yanhu;  Zhao, Xin;  Huang, Kaiqi
Adobe PDF(3484Kb)  |  收藏  |  浏览/下载：163/38  |  提交时间：2022/06/14
Skeleton-Based Action Recognition With Multi-Stream Adaptive Graph Convolutional Networks 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 期号: 29, 页码: 9532-9545
作者:  Shi, Lei;  Zhang, Yifan;  Cheng, Jian;  Lu, Hanqing
浏览  |  Adobe PDF(2849Kb)  |  收藏  |  浏览/下载：351/141  |  提交时间：2020/11/05
Skeleton-based action recognition, graph convolutional network, adaptive graph, multi-stream network.  
Attention Guided Multiple Source and Target Domain Adaptation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 期号: 30, 页码: 892-906
作者:  Wang, Yuxi;  Zhang, Zhaoxiang;  Hao, Wangli;  Song, Chunfeng
Adobe PDF(3460Kb)  |  收藏  |  浏览/下载：256/39  |  提交时间：2021/03/02
Semantics  Task analysis  Generators  Generative adversarial networks  Feature extraction  Visualization  Meteorology  Domain adaptation  multiple source and target domains  attention