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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：7/2  |  提交时间：2024/05/29
Weakly supervised object localization  intrinsic discrimination and consistency  deep metric learning  geometric transformation consistency  
Differentiable RandAugment: Learning Selecting Weights and Magnitude Distributions of Image Transformations 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 2413-2427
作者:  Xiao, Anqi;  Shen, Biluo;  Tian, Jie;  Hu, Zhenhua
收藏  |  浏览/下载：64/0  |  提交时间：2023/11/17
Task analysis  Training  Data models  Costs  Optimization  Search problems  Upper bound  Data augmentation  automated machine learning  differentiable optimization  random augmentation  
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：221/26  |  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：352/36  |  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  
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：182/42  |  提交时间：2022/06/14
An Efficient Sampling-Based Attention Network for Semantic Segmentation 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 2850-2863
作者:  He, Xingjian;  Liu, Jing;  Wang, Weining;  Lu, Hanqing
Adobe PDF(3252Kb)  |  收藏  |  浏览/下载：366/77  |  提交时间：2022/06/10
Stochastic processes  Sampling methods  Semantics  Image segmentation  Computational complexity  Pattern recognition  Convolution  Semantic segmentation  stochastic sampling-based attention  deterministic sampling-based attention  
Bifurcated Backbone Strategy for RGB-D Salient Object Detection 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 8727-8742
作者:  Zhai, Yingjie;  Fan, Deng-Ping;  Yang, Jufeng;  Borji, Ali;  Shao, Ling;  Han, Junwei;  Wang, Liang
收藏  |  浏览/下载：157/0  |  提交时间：2021/12/28
RGB-D salient object detection  bifurcated backbone strategy  multi-level features  cascaded refinement  
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：293/38  |  提交时间：2021/11/03
Urban reconstruction  building modeling  Markov random field  segment based modeling  
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：265/14  |  提交时间：2021/11/03
Skeleton-based action recognition  graph convolutional network  lightweight network  shift network  
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：266/57  |  提交时间：2021/11/02
Visualization  Semantics  Training  Feature extraction  Testing  Detectors  Predictive models  Zero-shot learning  transductive learning co-training