Vertex Feature Encoding and Hierarchical Temporal Modeling in a Spatio-Temporal Graph Convolutional Network for Action Recognition

Reference : Vertex Feature Encoding and Hierarchical Temporal Modeling in a Spatio-Temporal Graph...


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/44485

Title :	Vertex Feature Encoding and Hierarchical Temporal Modeling in a Spatio-Temporal Graph Convolutional Network for Action Recognition
Language :	English
Author, co-author :	Papadopoulos, Konstantinos [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
	Ghorbel, Enjie [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
	Aouada, Djamila [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2 >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2021
Main document title :	International Conference on Pattern Recognition, Milan 10-15 January 2021
Peer reviewed :	Yes
Event name :	25th International Conference on Pattern Recognition
Event date :	from 10-01-2021 to 15-01-2021
Permalink :	http://hdl.handle.net/10993/44485
FnR project :	FnR ; FNR10415355 > Bjorn Ottersten > 3D-ACT > 3D Action Recognition Using Refinement and Invariance Strategies for Reliable Surveillance > 01/06/2016 > 31/05/2019 > 2015

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Open access	ICPR20__home_papercept_iapr.papercept.net_www_conferences_conferences_ICPR20_submissions_0114_FI.pdf		Author preprint	412.25 kB	View/Open

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