CASIA OpenIR
Joint spatial-temporal attention for action recognition
Yu, Tingzhao1,2; Guo, Chaoxu1,2; Wang, Lingfeng1; Gu, Huxiang1; Xiang, Shiming1; Pan, Chunhong1
Source PublicationPATTERN RECOGNITION LETTERS
ISSN0167-8655
2018-09-01
Volume112Pages:226-233
SubtypeArticle
AbstractIn this paper, we propose a novel high-level action representation using joint spatial-temporal attention model, with application to video-based human action recognition. Specifically, to extract robust motion representations of videos, a new spatial attention module based on 3D convolution is proposed, which can pay attention to the salient parts of the spatial areas. For better dealing with long-duration videos, a new bidirectional LSTM based temporal attention module is introduced, which aims to focus on the key video cubes instead of the key video frames of a given video. The spatial-temporal attention network can be jointly trained via a two-stage strategy, which enables us to simultaneously explore the correlation both in spatial and temporal domain. Experimental results on benchmark action recognition datasets demonstrate the effectiveness of our network. (c) 2018 Elsevier B.V. All rights reserved.
KeywordAction Recognition Spatial-temporal Attention Two-stage
WOS HeadingsScience & Technology ; Technology
DOI10.1016/j.patrec.2018.07.034
WOS KeywordREPRESENTATION
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61773377 ; 61573352 ; 91646207 ; 91438105)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000443950800033
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/27907
Collection中国科学院自动化研究所
Corresponding AuthorYu, Tingzhao
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 101408, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yu, Tingzhao,Guo, Chaoxu,Wang, Lingfeng,et al. Joint spatial-temporal attention for action recognition[J]. PATTERN RECOGNITION LETTERS,2018,112:226-233.
APA Yu, Tingzhao,Guo, Chaoxu,Wang, Lingfeng,Gu, Huxiang,Xiang, Shiming,&Pan, Chunhong.(2018).Joint spatial-temporal attention for action recognition.PATTERN RECOGNITION LETTERS,112,226-233.
MLA Yu, Tingzhao,et al."Joint spatial-temporal attention for action recognition".PATTERN RECOGNITION LETTERS 112(2018):226-233.
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