A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation
dc.contributor.author
Gallego, Guillermo
dc.contributor.author
Rebecq, Henri
dc.contributor.author
Scaramuzza, Davide
dc.date.accessioned
2019-02-26T17:41:27Z
dc.date.available
2019-02-20T05:50:29Z
dc.date.available
2019-02-26T17:41:27Z
dc.date.issued
2018
dc.identifier.isbn
978-1-5386-6420-9
en_US
dc.identifier.isbn
978-1-5386-6421-6
en_US
dc.identifier.other
10.1109/CVPR.2018.00407
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/326356
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation
en_US
dc.type
Conference Paper
dc.date.published
2018-12-17
ethz.book.title
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
en_US
ethz.pages.start
3867
en_US
ethz.pages.end
3876
en_US
ethz.event
31st IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
en_US
ethz.event.location
Salt Lake City, UT, USA
en_US
ethz.event.date
June 18-23, 2018
en_US
ethz.identifier.wos
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2019-02-20T05:50:29Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
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ethz.rosetta.installDate
2019-02-26T17:41:36Z
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2019-02-26T17:41:36Z
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false
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true
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