CASIA OpenIR  > 智能感知与计算
Temporal sparse adversarial attack on sequence-based gait recognition
He, Ziwen1,2; Wang, Wei2,3; Dong, Jing2; Tan, Tieniu2
Source PublicationPATTERN RECOGNITION
ISSN0031-3203
2023
Volume133Pages:11
Corresponding AuthorWang, Wei(wwang@nlpr.ia.ac.cn)
AbstractGait recognition is widely used in social security applications due to its advantages in long-distance hu-man identification. Recently, sequence-based methods have achieved high accuracy by learning abundant temporal and spatial information. However, their robustness under adversarial attacks in an open world has not been clearly explored. In this paper, we demonstrate that the state-of-the-art gait recognition model is vulnerable to such attacks. To this end, we propose a novel temporal sparse adversarial attack method. Different from previous additive noise models which add perturbations on original samples, we employ a generative adversarial network based architecture to semantically generate adversarial high -quality gait silhouettes or video frames. Moreover, by sparsely substituting or inserting a few adversarial gait silhouettes, the proposed method ensures its imperceptibility and achieves a strong attack ability. The experimental results show that if only one-fortieth of the frames are attacked, the accuracy of the target model drops dramatically.(c) 2022 Elsevier Ltd. All rights reserved.
KeywordAdversarial attack Gait recognition Temporal sparsity
DOI10.1016/j.patcog.2022.109028
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Pro-gram of China ; National Natural Science Foundation of China ; [2021YFC3320103] ; [61972395]
Funding OrganizationNational Key Research and Development Pro-gram of China ; National Natural Science Foundation of China
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000870987900007
PublisherELSEVIER SCI LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/50509
Collection智能感知与计算
Corresponding AuthorWang, Wei
Affiliation1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Automat, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Inst Automat, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
He, Ziwen,Wang, Wei,Dong, Jing,et al. Temporal sparse adversarial attack on sequence-based gait recognition[J]. PATTERN RECOGNITION,2023,133:11.
APA He, Ziwen,Wang, Wei,Dong, Jing,&Tan, Tieniu.(2023).Temporal sparse adversarial attack on sequence-based gait recognition.PATTERN RECOGNITION,133,11.
MLA He, Ziwen,et al."Temporal sparse adversarial attack on sequence-based gait recognition".PATTERN RECOGNITION 133(2023):11.
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