Institute of Computing Technology, Chinese Academy IR
| Person Search by a Bi-Directional Task-Consistent Learning Model | |
| Wang, Cheng1; Ma, Bingpeng1; Chang, Hong2,3; Shan, Shiguang2,3,4; Chen, Xilin2,3 | |
| 2023 | |
| 发表期刊 | IEEE TRANSACTIONS ON MULTIMEDIA
![]() |
| ISSN | 1520-9210 |
| 卷号 | 25页码:1190-1203 |
| 摘要 | Two-stage person search methods achieve the state-of-the-art performance by separate detection and re-ID stages, but neglect the consistency needs between these two stages. The re-ID stage needs more accurate query bounding boxes and fewer boxes of distractors; The detection stage needs the re-ID stage to have robustness against unavailable detection errors. In this paper, we introduce a novel Bi-directional Task-Consistent Learning (BTCL) person search framework, including a Target-Specific Detector (TSD) and a re-ID model with Dynamic Adaptive Learning Structure (DALS). For the former consistency need, we add a verification head for predicting the similarity scores between query and proposals in parallel with the existing heads for bounding box recognition. Thus, TSD generates accurate boxes for the query-like pedestrians, which are suitable for the re-ID stage. For the re-ID robustness need, DALS dynamically generates a large number of possible detection results in line with the real distribution. By training the re-ID model on data with different types of detection errors, DLAS improves the model robustness to detection inputs. Experimental results show our framework achieves state-of-the-art performance on two widely-used person search datasets. |
| 关键词 | Task analysis Detectors Training Robustness Proposals Feature extraction Cameras Deep neural networks Person search |
| DOI | 10.1109/TMM.2021.3140025 |
| 收录类别 | SCI |
| 语种 | 英语 |
| 资助项目 | Natural Science Foundation of China (NSFC)[61876171] ; Natural Science Foundation of China (NSFC)[61976203] |
| WOS研究方向 | Computer Science ; Telecommunications |
| WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications |
| WOS记录号 | WOS:000970791100013 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://119.78.100.204/handle/2XEOYT63/21396 |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Ma, Bingpeng |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, CAS, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.CAS Ctr Excellence Brain Sci & Intelligence Techno, Shanghai 200031, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Cheng,Ma, Bingpeng,Chang, Hong,et al. Person Search by a Bi-Directional Task-Consistent Learning Model[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2023,25:1190-1203. |
| APA | Wang, Cheng,Ma, Bingpeng,Chang, Hong,Shan, Shiguang,&Chen, Xilin.(2023).Person Search by a Bi-Directional Task-Consistent Learning Model.IEEE TRANSACTIONS ON MULTIMEDIA,25,1190-1203. |
| MLA | Wang, Cheng,et al."Person Search by a Bi-Directional Task-Consistent Learning Model".IEEE TRANSACTIONS ON MULTIMEDIA 25(2023):1190-1203. |
| 条目包含的文件 | 条目无相关文件。 | |||||
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论