AIM 2020 Challenge on Image Extreme Inpainting
Evangelos Ntavelis, Andrés Romero, Siavash Bigdeli, Radu Timofte
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- github.com/vglsd/AIM2020-Image-Inpainting-ChallengeOfficialIn papernone★ 7
- github.com/Zheng222/DMFNpytorch★ 252
- github.com/Oorgien/Scene-Inpaintingpytorch★ 2
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 considerably large part of the image using no supervision but the context. Similarly, the goal of track 2 is to inpaint the image by having access to the entire semantic segmentation map of the image to inpaint. 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.