LUAI Challenge 2021 on Learning to Understand Aerial Images
Guisong Xia
Jian Ding
Ming Qian
Nan Xue
Jiaming Han
Xiang Bai
Micheal Ying Yang
Shengyang Li
Serge J. Belongie
Jiebo Luo
Mihai Datcu
Marcello Pelillo
Liangpei Zhang
Qiang-feng Zhou
Chao-hui Yu
Kaixuan Hu
Yingjia Bu
Wenming Tan
Zheng Yang
Wei Li
Shang Liu
Jiaxuan Zhao
T. Ma
Ziying Gao
Lingqi Wang
Yi Zuo
L. Jiao
Chang Meng
Hao Wang
Jiahao Wang
Yiming Hui
Zhuojun Dong
Jie Zhang
Qianyue Bao
Zixiao Zhang
Fang Liu

Abstract
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in aerial images. Using DOTA-v2.0 and GID-15 datasets, this challenge proposes three tasks for oriented object detection, horizontal object detection, and semantic segmentation of common categories in aerial images. This challenge received a total of 146 registrations on the three tasks. Through the challenge, we hope to draw attention from a wide range of communities and call for more efforts on the problems of learning to understand aerial images.
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