LUAI Challenge 2021 on Learning To Understand Aerial Images

Gui-Song Xia, Jian Ding, Ming Qian, Nan Xue, Jiaming Han, Xiang Bai, Michael Ying Yang, Shengyang Li, Serge Belongie, Jiebo Luo, Mihai Datcu, Marcello Pelillo, Liangpei Zhang; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021, pp. 762-768

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 seman tic segmentation in aerial images. Using DOTA-v2.0 [7]and GID-15 [35] datasets, this challenge proposes three tasks for oriented object detection, horizontal object detec-tion, 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.

Related Material

[pdf] [arXiv]
[bibtex]
@InProceedings{Xia_2021_ICCV, author = {Xia, Gui-Song and Ding, Jian and Qian, Ming and Xue, Nan and Han, Jiaming and Bai, Xiang and Yang, Michael Ying and Li, Shengyang and Belongie, Serge and Luo, Jiebo and Datcu, Mihai and Pelillo, Marcello and Zhang, Liangpei}, title = {LUAI Challenge 2021 on Learning To Understand Aerial Images}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {762-768} }