LUAI Challenge 2021 on Learning to Understand Aerial Images
| Autor: | Gui-Song Xia, Licheng Jiao, Lingqi Wang, Jiahao Wang, Zixiao Zhang, Tianzhi Ma, Fang Liu, Marcello Pelillo, Jiebo Luo, Wenming Tan, Xiang Bai, Serge Belongie, Jiaxuan Zhao, Zi-han Gao, Jiaming Han, Liangpei Zhang, Yiming Hui, Qianyue Bao, Shengyang Li, Hao Wang, Yi Zuo, Zhuojun Dong, Jian Ding, Kaixuan Hu, Chaohui Yu, Michael Ying Yang, Qiang Zhou, Shang Liu, Chang Meng, Jie Zhang, Yingjia Bu, Nan Xue, Zhe Yang, Wei Li, Mihai Datcu, Ming Qian |
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| Přispěvatelé: | Department of Earth Observation Science, UT-I-ITC-ACQUAL, Faculty of Geo-Information Science and Earth Observation |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Range (mathematics) Computer science business.industry Computer Vision and Pattern Recognition (cs.CV) Computer Science - Computer Vision and Pattern Recognition 22/2 OA procedure ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Computer vision Segmentation Artificial intelligence business Object detection |
| Zdroj: | Proceedings-2021 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021, 762-768 STARTPAGE=762;ENDPAGE=768;TITLE=Proceedings-2021 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021 |
| DOI: | 10.1109/iccvw54120.2021.00090 |
| Popis: | 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. 7 pages, 2 figures, accepted by ICCVW 2021 |
| Databáze: | OpenAIRE |
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