Abstract
We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks. The first track considered one-to-one relighting; the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation (i.e., light source position). The goal of the second track was to estimate illumination settings, namely the color temperature and orientation, from a given image. Lastly, the third track dealt with any-to-any relighting, thus a generalization of the first track. The target color temperature and orientation, rather than being pre-determined, are instead given by a guide image. Participants were allowed to make use of their track 1 and 2 solutions for track 3. The tracks had 94, 52, and 56 registered participants, respectively, leading to 20 confirmed submissions in the final competition stage.
Original language | English |
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Title of host publication | Computer Vision – ECCV 2020 Workshops, Proceedings |
Editors | Adrien Bartoli, Andrea Fusiello |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 499-518 |
Number of pages | 20 |
ISBN (Print) | 9783030670696 |
DOIs | |
State | Published - 2020 |
Event | Workshops held at the 16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom Duration: 23 Aug 2020 → 28 Aug 2020 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12537 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | Workshops held at the 16th European Conference on Computer Vision, ECCV 2020 |
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Country/Territory | United Kingdom |
City | Glasgow |
Period | 23/08/20 → 28/08/20 |
Keywords
- Illumination estimation
- Image relighting
- Style transfer