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Grammar-Induced Wavelet Network for Human Parsing 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 期号: 31, 页码: 4502-4514
作者:  Xiaomei Zhang;  Yingying Chen;  Ming Tang;  Zhen Lei;  Jinqiao Wang
Adobe PDF(3308Kb)  |  收藏  |  浏览/下载：37/13  |  提交时间：2024/06/03
Exploring Intrinsic Discrimination and Consistency for Weakly Supervised Object Localization 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2024, 卷号: 33, 期号: 0, 页码: 1045 - 1058
作者:  Changwei Wang;  Rongtao Xu;  Shibiao Xu;  Weiliang Meng;  Ruisheng Wang;  Xiaopeng Zhang
Adobe PDF(3269Kb)  |  收藏  |  浏览/下载：55/17  |  提交时间：2024/05/29
Weakly supervised object localization  intrinsic discrimination and consistency  deep metric learning  geometric transformation consistency  
Coarse Mask Guided Interactive Object Segmentation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 5808-5822
作者:  Li, Jing;  Fan, Junsong;  Wang, Yuxi;  Yang, Yuran;  Zhang, Zhaoxiang
Adobe PDF(4323Kb)  |  收藏  |  浏览/下载：55/3  |  提交时间：2024/02/22
Segmentation  interactive  transformer  annotation tool  
Reducing Vision-Answer Biases for Multiple-Choice VQA 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 4621-4634
作者:  Zhang, Xi;  Zhang, Feifei;  Xu, Changsheng
Adobe PDF(2684Kb)  |  收藏  |  浏览/下载：84/2  |  提交时间：2023/11/17
Multiple-choice VQA  vision-answer bias  causal intervention  counterfactual interaction learning  
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：273/34  |  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  
Mixed-Supervised Scene Text Detection With Expectation-Maximization Algorithm 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 5513-5528
作者:  Zhao, Mengbiao;  Feng, Wei;  Yin, Fei;  Zhang, Xu-Yao;  Liu, Cheng-Lin
Adobe PDF(5999Kb)  |  收藏  |  浏览/下载：443/42  |  提交时间：2022/09/19
Costs  Annotations  Training  Labeling  Detectors  Data models  Benchmark testing  Mixed-supervised learning  scene text detection  weak supervision forms  expectation-maximization algorithm  
Efficient Center Voting for Object Detection and 6D Pose Estimation in 3D Point Cloud 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 期号: 1, 页码: 5072-5084
作者:  Guo, Jianwei;  Xing, Xuejun;  Quan, Weize;  Yan, Dong-Ming;  Gu, Qingyi;  Liu, Yang;  Zhang, Xiaopeng
Adobe PDF(8313Kb)  |  收藏  |  浏览/下载：224/7  |  提交时间：2021/08/15
Three-dimensional displays  Pose estimation  Shape  Object detection  Feature extraction  Object recognition  Transmission line matrix methods  6D pose estimation  3D object recognition  point pair features  3D point cloud  
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：209/59  |  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  
Attention-Based Pedestrian Attribute Analysis 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 12, 页码: 6126-6140
作者:  Zichang Tan;  Yang Yang;  Jun Wan;  Hanyuan Hang;  Guodong Guo;  Stan Z. Li
Adobe PDF(3457Kb)  |  收藏  |  浏览/下载：249/48  |  提交时间：2020/10/27
Pedestrian attribute analysis  attention mechanism  pedestrian parsing  
Mask SSD: An Effective Single-Stage Approach to Object Instance Segmentation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 期号: 1, 页码: 2078-2093
作者:  Zhang, Hui;  Tian, Yonglin;  Wang, Kunfeng;  Zhang, Wensheng;  Wang, Fei-Yue
浏览  |  Adobe PDF(4983Kb)  |  收藏  |  浏览/下载：378/165  |  提交时间：2020/03/30
Object detection  instance segmentation  feedback features  single-shot detector