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dc.contributor.author
Arad, Boaz
dc.contributor.author
Timofte, Radu
dc.contributor.author
Ben-Shahar, Ohad
dc.contributor.author
Lin, Yi-Tun
dc.contributor.author
Finlayson, Graham
dc.contributor.author
Givati, Shai
dc.contributor.author
et al.
dc.date.accessioned
2020-09-14T08:43:02Z
dc.date.available
2020-09-10T05:45:08Z
dc.date.available
2020-09-14T08:43:02Z
dc.date.issued
2020
dc.identifier.isbn
978-1-7281-9360-1
en_US
dc.identifier.isbn
978-1-7281-9361-8
en_US
dc.identifier.other
10.1109/CVPRW50498.2020.00231
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/439477
dc.description.abstract
This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole- scene hyperspectral (HS) information from a 3-channel RGB image. As in the previous challenge, two tracks were provided: (i) a "Clean" track where HS images are estimated from noise-free RGBs, the RGB images are themselves calculated numerically using the ground-truth HS images and supplied spectral sensitivity functions (ii) a "Real World" track, simulating capture by an uncalibrated and unknown camera, where the HS images are recovered from noisy JPEG-compressed RGB images. A new, larger-than-ever, natural hyperspectral image data set is presented, containing a total of 510 HS images. The Clean and Real World tracks had 103 and 78 registered participants respectively, with 14 teams competing in the final testing phase. A description of the proposed methods, alongside their challenge scores and an extensive evaluation of top performing methods is also provided. They gauge the state-of-the-art in spectral reconstruction from an RGB image. © 2020 IEEE.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
NTIRE 2020 challenge on spectral reconstruction from an RGB image
en_US
dc.type
Conference Paper
dc.date.published
2020-07-28
ethz.book.title
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
en_US
ethz.pages.start
1806
en_US
ethz.pages.end
1822
en_US
ethz.event
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2020) (virtual)
en_US
ethz.event.location
Seattle, WA, USA
en_US
ethz.event.date
June 14-19, 2020
en_US
ethz.notes
Due to the Corona virus (COVID-19) the conference was conducted virtually.
en_US
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2020-09-10T05:45:35Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-09-14T08:43:21Z
ethz.rosetta.lastUpdated
2020-09-14T08:43:21Z
ethz.rosetta.versionExported
true
ethz.COinS
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