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dc.contributor.author
Wang, Limin
dc.contributor.author
Xiong, Yuanjun
dc.contributor.author
Lin, Dahua
dc.contributor.author
Van Gool, Luc
dc.date.accessioned
2018-01-30T11:44:58Z
dc.date.available
2018-01-11T02:32:27Z
dc.date.available
2018-01-30T11:44:58Z
dc.date.available
2018-01-24T10:42:45Z
dc.date.available
2018-01-30T11:42:46Z
dc.date.issued
2017
dc.identifier.isbn
978-1-5386-0457-1
en_US
dc.identifier.isbn
978-1-5386-0458-8
en_US
dc.identifier.other
10.1109/CVPR.2017.678
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/238023
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
UntrimmedNets for Weakly Supervised Action Recognition and Detection
en_US
dc.type
Conference Paper
ethz.book.title
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
en_US
ethz.pages.start
6402
en_US
ethz.pages.end
6411
en_US
ethz.event
30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017)
en_US
ethz.event.location
Honolulu, HI, USA
en_US
ethz.event.date
July 21-26, 2016
en_US
ethz.identifier.wos
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Departement Informationstechnologie und Elektrotechnik / Department of Information Technology and Electrical Engineering::02652 - Institut für Bildverarbeitung / Computer Vision Laboratory
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Departement Informationstechnologie und Elektrotechnik / Department of Information Technology and Electrical Engineering::02652 - Institut für Bildverarbeitung / Computer Vision Laboratory::03514 - Van Gool, Luc
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Departement Informationstechnologie und Elektrotechnik / Department of Information Technology and Electrical Engineering::02652 - Institut für Bildverarbeitung / Computer Vision Laboratory::03514 - Van Gool, Luc
ethz.date.deposited
2018-01-11T02:33:03Z
ethz.source
WOS
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2018-02-01T11:41:15Z
ethz.rosetta.lastUpdated
2018-02-01T11:41:15Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/233538
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/227373
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=UntrimmedNets%20for%20Weakly%20Supervised%20Action%20Recognition%20and%20Detection&rft.date=2017&rft.spage=6402&rft.epage=6411&rft.au=Wang,%20Limin&Xiong,%20Yuanjun&Lin,%20Dahua&Van%20Gool,%20Luc&rft.isbn=978-1-5386-0457-1&978-1-5386-0458-8&rft.genre=proceeding&rft_id=info:doi/978-1-5386-0457-1&info:doi/978-1-5386-0458-8&rft.btitle=2017%20IEEE%20Conference%20on%20Computer%20Vision%20and%20Pattern%20Recognition%20(CVPR)
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