论文标题
AIM 2020挑战在图像极端涂到图像上
AIM 2020 Challenge on Image Extreme Inpainting
论文作者
论文摘要
本文回顾了AIM 2020挑战在极端图像上介绍。本报告着重于对极端图像介绍的两个不同轨道的建议解决方案和结果：经典图像介入和语义引导的图像插图。轨道1的目的是使用无监督，而是上下文，以大量图像进行绘制。同样，轨道2的目的是通过访问图像的整个语义分割图来对图像进行涂漆。挑战分别有88名和74名参与者。 11和6球队分别参加了挑战的最后阶段。该报告衡量了当前的解决方案，并为将来的极端图像介入方法设定了基准。
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.
