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.
Original language | English |
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Title of host publication | Proceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 |
Place of Publication | Piscataway, N.J. |
Pages | 1806-1822 |
Number of pages | 17 |
ISBN (Electronic) | 9781728193601 |
DOIs | |
Publication status | Published - 28 Jul 2020 |
Event | 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 - Virtual, Online, United States Duration: 14 Jun 2020 → 19 Jun 2020 |
Conference
Conference | 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 |
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Country/Territory | United States |
City | Virtual, Online |
Period | 14/06/20 → 19/06/20 |
Keywords
- RGB images
- RGB colour system
- spectral images
- spectral scanning