CASIA OpenIR

浏览/检索结果: 共36条,第1-10条 帮助

限定条件        
已选(0)清除 条数/页:   排序方式:
Multi-Stage Image-Language Cross-Generative Fusion Network for Video-Based Referring Expression Comprehension 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2024, 卷号: 33, 页码: 3256-3270
作者:  Zhang, Yujia;  Li, Qianzhong;  Pan, Yi;  Zhao, Xiaoguang;  Tan, Min
收藏  |  浏览/下载:9/0  |  提交时间:2024/07/03
Feature extraction  Visualization  Task analysis  Representation learning  Location awareness  Linguistics  Grounding  Video-based referring expression comprehension  multi-stage learning  image-language cross-generative fusion  consistency loss  
General vs. Long-Tailed Age Estimation: An Approach to Kill Two Birds With One Stone 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 6155-6167
作者:  Bao, Zenghao;  Tan, Zichang;  Li, Jun;  Wan, Jun;  Ma, Xibo;  Lei, Zhen
Adobe PDF(1634Kb)  |  收藏  |  浏览/下载:56/2  |  提交时间:2024/02/22
General age estimation  long-tailed age estimation  class-wise mean absolute error  
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:63/4  |  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:90/5  |  提交时间:2023/11/17
Multiple-choice VQA  vision-answer bias  causal intervention  counterfactual interaction learning  
Cross-Batch Hard Example Mining With Pseudo Large Batch for ID vs. Spot Face Recognition 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 3224-3235
作者:  Tan, Zichang;  Liu, Ajian;  Wan, Jun;  Liu, Hao;  Lei, Zhen;  Guo, Guodong;  Li, Stan Z.
Adobe PDF(10124Kb)  |  收藏  |  浏览/下载:290/5  |  提交时间:2022/07/25
Face recognition  Training  Measurement  Graphics processing units  Deep learning  Logic gates  Feature extraction  Face recognition  ID vs spot  deep learning  cross-batch hard example mining  pseudo large batch  
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:206/48  |  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:398/80  |  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  
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:324/43  |  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:297/16  |  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:297/66  |  提交时间:2021/11/02
Visualization  Semantics  Training  Feature extraction  Testing  Detectors  Predictive models  Zero-shot learning  transductive learning co-training