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Cycle-Consistent Weakly Supervised Visual Grounding With Individual and Contextual Representations 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 5167-5180
作者:  Zhang, Ruisong;  Wang, Chuang;  Liu, Cheng-Lin
收藏  |  浏览/下载：93/0  |  提交时间：2023/11/16
Visualization  Grounding  Task analysis  Sports equipment  Image reconstruction  Transformers  Training  Weakly supervised learning  visual grounding  cycle consistency  individual and contextual representations  
Learning Domain Invariant Representations for Generalizable Person Re-Identification 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 509-523
作者:  Zhang, Yi-Fan;  Zhang, Zhang;  Li, Da;  Jia, Zhen;  Wang, Liang;  Tan, Tieniu
收藏  |  浏览/下载：183/0  |  提交时间：2023/03/20
Generalizable person re-Identification  disentanglement  backdoor adjustment  
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  
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：286/34  |  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：169/38  |  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：334/75  |  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  
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：273/0  |  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-Modality Self-Distillation for Weakly Supervised Temporal Action Localization 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 1504-1519
作者:  Huang, Linjiang;  Wang, Liang;  Li, Hongsheng
收藏  |  浏览/下载：190/0  |  提交时间：2022/03/17
Location awareness  Reliability  Noise measurement  Annotations  Training  Head  Task analysis  Weakly supervised temporal action localization  multi-modality  pseudo label  self-distillation  
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：248/32  |  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：233/52  |  提交时间：2021/11/02
Visualization  Semantics  Training  Feature extraction  Testing  Detectors  Predictive models  Zero-shot learning  transductive learning co-training