Benchmarking sensitivity of continual graph learning for skeleton-based action recognition

dc.contributor.author	Wei, W.
dc.contributor.author	De Schepper, Tom
dc.contributor.author	Mets, Kevin
dc.contributor.imecauthor	De Schepper, Tom
dc.contributor.imecauthor	Mets, Kevin
dc.contributor.orcidimec	De Schepper, Tom::0000-0002-2969-3133
dc.contributor.orcidimec	Mets, Kevin::0000-0002-4812-4841
dc.date.accessioned	2025-01-20T10:49:59Z
dc.date.available	2025-01-20T10:49:59Z
dc.date.issued	2024
dc.identifier.doi	10.5220/0012394400003660
dc.identifier.eisbn	978-989-758-679-8
dc.identifier.issn	2184-4321
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/45096
dc.publisher	SciTePress
dc.source.beginpage	639
dc.source.conference	VISIGRAPP 2024 : Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
dc.source.conferencedate	27-29 February 2024
dc.source.conferencelocation	Rome
dc.source.endpage	651
dc.source.journal	N/A
dc.source.numberofpages	13
dc.title	Benchmarking sensitivity of continual graph learning for skeleton-based action recognition
dc.type	Proceedings paper
dspace.entity.type	Publication
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