Knowledge Commons of Institute of Automation,CAS
Dual Instance-Consistent Network for Cross-Domain Object Detection | |
Jiao, Yifan1; Yao, Hantao2; Xu, Changsheng3,4,5 | |
发表期刊 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE |
ISSN | 0162-8828 |
2023-06-01 | |
卷号 | 45期号:6页码:7338-7352 |
通讯作者 | Xu, Changsheng(csxu@nlpr.ia.ac.cn) |
摘要 | Cross-domain object detection aims to transfer knowledge from a labeled dataset to an unlabeled dataset. Most existing methods apply a unified embedding model to generate the tightly coupled source and target descriptions for domain alignment, leading to the destroyed feature distribution of the target domain because the embedding model is mainly controlled by the source domain. To reduce the representation bias of the target domain, we apply two independent networks to extract two types of discriminative descriptions with mutual consistency, i.e., a novel Dual Instance-Consistent Network (DICN) is proposed for cross-domain object detection. Especially, Dual Instance-Consistent Module containing the instance mutual consistency between Primary Network and Auxiliary Network is applied to align two domains, where Primary and Auxiliary Networks are used to obtain the source-specific and target-specific information, respectively. The instance mutual consistency consists of two terms: feature consistency and detection consistency, which is applied to align the instance feature and the output of detection head, respectively. With the instance mutual consistency, optimizing the Primary (Auxiliary) Network only with source (target) images by fixing the Auxiliary (Primary) Network can generate the source(target)-specific description. Extensive experiments on several benchmarks demonstrate the effectiveness of the proposed DICN, e.g., obtaining mAP of 44.10% for Cityscapes-> Foggy Cityscapes, AP on car of 76.50% for Cityscapes-> KITTI, MR (2) of 8.87%, 12.66%, 22.27%, and 42.06% for COCOPersons-> Caltech, CityPersons-> Caltech, COCOPersons-> CityPersons, and Caltech-> CityPersons, respectively. |
关键词 | Feature extraction Object detection Detectors Visualization Proposals Head Task analysis Cross-domain object detection domain-specific description dual instance-consistent network |
DOI | 10.1109/TPAMI.2022.3218569 |
关键词[WOS] | ALIGNMENT |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2020AAA0106200] ; National Natural Science Foundation of China[61902399] ; National Natural Science Foundation of China[U21B2044] ; National Natural Science Foundation of China[U1836220] ; National Natural Science Foundation of China[61721004] ; National Natural Science Foundation of China[62002355] ; National Natural Science Foundation of China[61936005] ; Beijing Natural Science Foundation[L201001] ; Beijing Natural Science Foundation[4222039] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000982475600049 |
出版者 | IEEE COMPUTER SOC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/53520 |
专题 | 多模态人工智能系统全国重点实验室 |
通讯作者 | Xu, Changsheng |
作者单位 | 1.Nanjing Univ Posts & Telecommun, Sch Commun & Informat Engn, Nanjing, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Automation, Natl Lab Pattern Recognit, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 5.Peng Cheng Lab, Shenzhen 518055, Peoples R China |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Jiao, Yifan,Yao, Hantao,Xu, Changsheng. Dual Instance-Consistent Network for Cross-Domain Object Detection[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2023,45(6):7338-7352. |
APA | Jiao, Yifan,Yao, Hantao,&Xu, Changsheng.(2023).Dual Instance-Consistent Network for Cross-Domain Object Detection.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,45(6),7338-7352. |
MLA | Jiao, Yifan,et al."Dual Instance-Consistent Network for Cross-Domain Object Detection".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 45.6(2023):7338-7352. |
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