AIM 2020 Challenge on Image Extreme Inpainting
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Author / Producer
Date
2020
Publication Type
Conference Paper
ETH Bibliography
yes
Citations
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Abstract
This paper reviews the AIM 2020 challenge on extreme image inpainting. This report focuses on proposed solutions and results for two different tracks on extreme image inpainting: classical image inpainting and semantically guided image inpainting. The goal of track 1 is to inpaint large part of the image with no supervision. Similarly, the goal of track 2 is to inpaint the image by having access to the entire semantic segmentation map of the input. The challenge had 88 and 74 participants, respectively. 11 and 6 teams competed in the final phase of the challenge, respectively. This report gauges current solutions and set a benchmark for future extreme image inpainting methods.
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Publication status
published
External links
Book title
Computer Vision – ECCV 2020 Workshops
Journal / series
Volume
12537
Pages / Article No.
716 - 741
Publisher
Springer
Event
European Conference on Computer Vision Workshops (ECCVW 2020) (virtual)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Extreme image inpainting; Image synthesis; Generative modeling
Organisational unit
03514 - Van Gool, Luc (emeritus) / Van Gool, Luc (emeritus)
Notes
Due to the Coronavirus (COVID-19) the workshop was conducted virtually.