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Narrowing the Gap: Improved Detector Training With Noisy Location Annotations 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 6369-6380
作者:  Wang, Shaoru;  Gao, Jin;  Li, Bing;  Hu, Weiming
Adobe PDF(1489Kb)  |  收藏  |  浏览/下载：195/23  |  提交时间：2022/11/14
Annotations  Noise measurement  Detectors  Task analysis  Training  Object detection  Degradation  Object detection  noisy label  Bayesian estimation  teacher-student learning  
Image Inpainting With Local and Global Refinement 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 2405-2420
作者:  Quan, Weize;  Zhang, Ruisong;  Zhang, Yong;  Li, Zhifeng;  Wang, Jue;  Yan, Dong-Ming
收藏  |  浏览/下载：272/0  |  提交时间：2022/06/06
Image reconstruction  Generators  Convolution  Semantics  Image edge detection  Deep learning  Task analysis  Image inpainting  neural networks  receptive field  
Multi-Scale Low-Discriminative Feature Reactivation for Weakly Supervised Object Localization 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 6050-6065
作者:  Wang, Bo;  Yuan, Chunfeng;  Li, Bing;  Ding, Xinmiao;  Li, Zeya;  Wu, Ying;  Hu, Weiming
收藏  |  浏览/下载：188/0  |  提交时间：2021/08/15
Location awareness  Neurons  Task analysis  Pattern recognition  Automation  Search problems  Proposals  Weakly supervised object localization  feature recalibration  multi-scale class activation mapping  
Anisotropic Convolution for Image Classification 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 期号: 99, 页码: 5584-5595
作者:  Li, Wenjuan;  Li, Bing;  Yuan, Chunfeng;  Li, Yangxi;  Wu, Haohao;  Hu, Weiming;  Wang, Fangshi
收藏  |  浏览/下载：169/0  |  提交时间：2020/10/16
Anisotropic convolution  image classification  object localization  
Multi-Cue Semi-Supervised Color Constancy With Limited Training Samples 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7875-7888
作者:  Huang, Xinwei;  Li, Bing;  Li, Shuai;  Li, Wenjuan;  Xiong, Weihua;  Yin, Xuanwu;  Hu, Weiming;  Qin, Hong
收藏  |  浏览/下载：191/0  |  提交时间：2020/08/24
Color constancy  illumination estimation  white balancing  multi-cue  semi-supervised  
Efficient Single-Stage Pedestrian Detector by Asymptotic Localization Fitting and Multi-Scale Context Encoding 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 1413-1425
作者:  Liu, Wei;  Liao, Shengcai;  Hu, Weidong
收藏  |  浏览/下载：192/0  |  提交时间：2020/03/30
Pedestrian detection  convolutional neural networks  asymptotic localization fitting  
Anisotropic Convolution for Image Classification 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 5584-5595
作者:  Li, Wenjuan;  Li, Bing;  Yuan, Chunfeng;  Li, Yangxi;  Wu, Haohao;  Hu, Weiming;  Wang, Fangshi
收藏  |  浏览/下载：244/0  |  提交时间：2020/06/22
Convolution  Shape  Kernel  Feature extraction  Task analysis  Training  Neural networks  Anisotropic convolution  image classification  object localization  
STA-CNN: Convolutional Spatial-Temporal Attention Learning for Action Recognition 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 5783-5793
作者:  Yang, Hao;  Yuan, Chunfeng;  Zhang, Li;  Sun, Yunda;  Hu, Weiming;  Maybank, Stephen J.
收藏  |  浏览/下载：275/0  |  提交时间：2020/06/22
Videos  Feature extraction  Motion segmentation  Computational modeling  Image recognition  Solid modeling  Convolutional neural networks  Temporal attention  spatial attention  convolutional neural network  action recognition  
A Richly Annotated Pedestrian Dataset for Person Retrieval in Real Surveillance Scenarios 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 4, 页码: 1575-1590
作者:  Li, Dangwei;  Zhang, Zhang;  Chen, Xiaotang;  Huang, Kaiqi
收藏  |  浏览/下载：315/0  |  提交时间：2019/07/12
Pedestrian retrieval  person re-identification  pedestrian attribute recognition  multi-label learning  
Context-Dependent Random Walk Graph Kernels and Tree Pattern Graph Matching Kernels With Applications to Action Recognition 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 卷号: 27, 期号: 10, 页码: 5060-5075
作者:  Hu, Weiming;  Wu, Baoxin;  Wang, Pei;  Yuan, Chunfeng;  Li, Yangxi;  Maybank, Stephen
收藏  |  浏览/下载：237/0  |  提交时间：2019/12/16
Visual action recognition  graph kernel  graph matching  contexts  tree patterns