Standard
LUAI Challenge 2021 on Learning to Understand Aerial Images. / Xia, Gui Song; Ding, Jian; Qian, Ming; Xue, Nan; Han, Jiaming; Bai, Xiang; Yang, Michael Ying; Li, Shengyang; Belongie, Serge; Luo, Jiebo; Datcu, Mihai; Pelillo, Marcello; Zhang, Liangpei; Zhou, Qiang; Yu, Chao Hui; Hu, Kaixuan; Bu, Yingjia; Tan, Wenming; Yang, Zhe; Li, Wei; Liu, Shang; Zhao, Jiaxuan; Ma, Tianzhi; Gao, Zi Han; Wang, Lingqi; Zuo, Yi; Jiao, Licheng; Meng, Chang; Wang, Hao; Wang, Jiahao; Hui, Yiming; Dong, Zhuojun; Zhang, Jie; Bao, Qianyue; Zhang, Zixiao; Liu, Fang.
2021 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). IEEE, 2021. p. 762-768.
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Xia, GS, Ding, J, Qian, M, Xue, N, Han, J, Bai, X, Yang, MY, Li, S
, Belongie, S, Luo, J, Datcu, M, Pelillo, M, Zhang, L, Zhou, Q, Yu, CH, Hu, K, Bu, Y, Tan, W, Yang, Z, Li, W, Liu, S, Zhao, J, Ma, T, Gao, ZH, Wang, L, Zuo, Y, Jiao, L, Meng, C, Wang, H, Wang, J, Hui, Y, Dong, Z, Zhang, J, Bao, Q, Zhang, Z & Liu, F 2021,
LUAI Challenge 2021 on Learning to Understand Aerial Images. in
2021 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). IEEE, pp. 762-768, 18th IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021, Virtual, Online, Canada,
11/10/2021.
https://doi.org/10.1109/ICCVW54120.2021.00090APA
Xia, G. S., Ding, J., Qian, M., Xue, N., Han, J., Bai, X., Yang, M. Y., Li, S.
, Belongie, S., Luo, J., Datcu, M., Pelillo, M., Zhang, L., Zhou, Q., Yu, C. H., Hu, K., Bu, Y., Tan, W., Yang, Z., ... Liu, F. (2021).
LUAI Challenge 2021 on Learning to Understand Aerial Images. In
2021 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) (pp. 762-768). IEEE.
https://doi.org/10.1109/ICCVW54120.2021.00090Vancouver
Xia GS, Ding J, Qian M, Xue N, Han J, Bai X et al.
LUAI Challenge 2021 on Learning to Understand Aerial Images. In 2021 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). IEEE. 2021. p. 762-768
https://doi.org/10.1109/ICCVW54120.2021.00090Author
Xia, Gui Song ; Ding, Jian ; Qian, Ming ; Xue, Nan ; Han, Jiaming ; Bai, Xiang ; Yang, Michael Ying ; Li, Shengyang ; Belongie, Serge ; Luo, Jiebo ; Datcu, Mihai ; Pelillo, Marcello ; Zhang, Liangpei ; Zhou, Qiang ; Yu, Chao Hui ; Hu, Kaixuan ; Bu, Yingjia ; Tan, Wenming ; Yang, Zhe ; Li, Wei ; Liu, Shang ; Zhao, Jiaxuan ; Ma, Tianzhi ; Gao, Zi Han ; Wang, Lingqi ; Zuo, Yi ; Jiao, Licheng ; Meng, Chang ; Wang, Hao ; Wang, Jiahao ; Hui, Yiming ; Dong, Zhuojun ; Zhang, Jie ; Bao, Qianyue ; Zhang, Zixiao ; Liu, Fang. / LUAI Challenge 2021 on Learning to Understand Aerial Images. 2021 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). IEEE, 2021. pp. 762-768
Bibtex
@inproceedings{0334216b348e41e9ba0cdc6dfcfe0074,
title = "LUAI Challenge 2021 on Learning to Understand Aerial Images",
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 [7] and GID-15 [35] 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. ",
author = "Xia, {Gui Song} and Jian Ding and Ming Qian and Nan Xue and Jiaming Han and Xiang Bai and Yang, {Michael Ying} and Shengyang Li and Serge Belongie and Jiebo Luo and Mihai Datcu and Marcello Pelillo and Liangpei Zhang and Qiang Zhou and Yu, {Chao Hui} and Kaixuan Hu and Yingjia Bu and Wenming Tan and Zhe Yang and Wei Li and Shang Liu and Jiaxuan Zhao and Tianzhi Ma and Gao, {Zi Han} and Lingqi Wang and Yi Zuo and Licheng Jiao and Chang Meng and Hao Wang and Jiahao Wang and Yiming Hui and Zhuojun Dong and Jie Zhang and Qianyue Bao and Zixiao Zhang and Fang Liu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021 ; Conference date: 11-10-2021 Through 17-10-2021",
year = "2021",
doi = "10.1109/ICCVW54120.2021.00090",
language = "English",
pages = "762--768",
booktitle = "2021 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
publisher = "IEEE",
}
RIS
TY - GEN
T1 - LUAI Challenge 2021 on Learning to Understand Aerial Images
AU - Xia, Gui Song
AU - Ding, Jian
AU - Qian, Ming
AU - Xue, Nan
AU - Han, Jiaming
AU - Bai, Xiang
AU - Yang, Michael Ying
AU - Li, Shengyang
AU - Belongie, Serge
AU - Luo, Jiebo
AU - Datcu, Mihai
AU - Pelillo, Marcello
AU - Zhang, Liangpei
AU - Zhou, Qiang
AU - Yu, Chao Hui
AU - Hu, Kaixuan
AU - Bu, Yingjia
AU - Tan, Wenming
AU - Yang, Zhe
AU - Li, Wei
AU - Liu, Shang
AU - Zhao, Jiaxuan
AU - Ma, Tianzhi
AU - Gao, Zi Han
AU - Wang, Lingqi
AU - Zuo, Yi
AU - Jiao, Licheng
AU - Meng, Chang
AU - Wang, Hao
AU - Wang, Jiahao
AU - Hui, Yiming
AU - Dong, Zhuojun
AU - Zhang, Jie
AU - Bao, Qianyue
AU - Zhang, Zixiao
AU - Liu, Fang
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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 [7] and GID-15 [35] 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.
AB - 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 [7] and GID-15 [35] 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.
UR - http://www.scopus.com/inward/record.url?scp=85123053865&partnerID=8YFLogxK
U2 - 10.1109/ICCVW54120.2021.00090
DO - 10.1109/ICCVW54120.2021.00090
M3 - Article in proceedings
AN - SCOPUS:85123053865
SP - 762
EP - 768
BT - 2021 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
PB - IEEE
T2 - 18th IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021
Y2 - 11 October 2021 through 17 October 2021
ER -
