Multi-branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions

dc.contributor.author	Leroux, Sam
dc.contributor.author	Li, Bo
dc.contributor.author	Simoens, Pieter
dc.contributor.imecauthor	Leroux, Sam
dc.contributor.imecauthor	Li, Bo
dc.contributor.imecauthor	Simoens, Pieter
dc.contributor.orcidimec	Leroux, Sam::0000-0003-3792-5026
dc.contributor.orcidimec	Simoens, Pieter::0000-0002-9569-9373
dc.date.accessioned	2022-11-28T11:13:11Z
dc.date.available	2022-07-07T02:27:26Z
dc.date.available	2022-07-07T06:12:21Z
dc.date.available	2022-11-28T11:13:11Z
dc.date.issued	2022
dc.description.wosFundingText	This research received funding from the Flemish Government under the "Onderzoeksprogramma Artificiele Intelligentie (AI) Vlaanderen" programme, and from imec under the CityFlows AAA programme.
dc.identifier.doi	10.1109/WACV51458.2022.00308
dc.identifier.eisbn	978-1-6654-0915-5
dc.identifier.issn	2472-6737
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/40069
dc.publisher	IEEE COMPUTER SOC
dc.source.beginpage	3027
dc.source.conference	22nd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
dc.source.conferencedate	JAN 04-08, 2022
dc.source.conferencelocation	Waikoloa
dc.source.endpage	3035
dc.source.journal	/
dc.source.numberofpages	9
dc.title	Multi-branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions
dc.type	Proceedings paper
dspace.entity.type	Publication
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