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VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results

19 July 2021
Dawei Du
Longyin Wen
Pengfei Zhu
Heng Fan
Q. Hu
Haibin Ling
M. Shah
Junwen Pan
Ali Al-Ali
Amr M. Mohamed
Bakour Imene
Bin Dong
Binyu Zhang
Bouchali Hadia Nesma
Chenfeng Xu
Chenzhen Duan
C. Castiello
Corrado Mencar
Dingkang Liang
F. Krüger
G. Vessio
Giovanna Castellano
Jieru Wang
Junyu Gao
Khalid Abualsaud
Laihui Ding
Lei Zhao
Marco Cianciotta
M. Saqib
Noor Almaadeed
O. Elharrouss
Pei Lyu
Qi. Wang
Shidong Liu
Shuang Qiu
Siyang Pan
S. Al-Maadeed
Sultan Daud Khan
T. Khattab
T. Han
T. Golda
W. Xu
Xiang Bai
Xiaoqing Xu
Xuelong Li
Yanyun Zhao
Ye Tian
Ying-wu Lin
Yongchao Xu
Yuehan Yao
Zhenyu Xu
Zhijian Zhao
Zhipeng Luo
Zhiwei Wei
Zhiyuan Zhao
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Abstract

Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint. However, there are few algorithms focusing on crowd counting on the drone-captured data due to the lack of comprehensive datasets. To this end, we collect a large-scale dataset and organize the Vision Meets Drone Crowd Counting Challenge (VisDrone-CC2020) in conjunction with the 16th European Conference on Computer Vision (ECCV 2020) to promote the developments in the related fields. The collected dataset is formed by 3,3603,3603,360 images, including 2,4602,4602,460 images for training, and 900900900 images for testing. Specifically, we manually annotate persons with points in each video frame. There are 141414 algorithms from 151515 institutes submitted to the VisDrone-CC2020 Challenge. We provide a detailed analysis of the evaluation results and conclude the challenge. More information can be found at the website: \url{http://www.aiskyeye.com/}.

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