VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
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 images, including images for training, and images for testing. Specifically, we manually annotate persons with points in each video frame. There are algorithms from 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/}.
Cite
@article{arxiv.2107.08766,
title = {VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results},
author = {Dawei Du and Longyin Wen and Pengfei Zhu and Heng Fan and Qinghua Hu and Haibin Ling and Mubarak Shah and Junwen Pan and Ali Al-Ali and Amr Mohamed and Bakour Imene and Bin Dong and Binyu Zhang and Bouchali Hadia Nesma and Chenfeng Xu and Chenzhen Duan and Ciro Castiello and Corrado Mencar and Dingkang Liang and Florian Krüger and Gennaro Vessio and Giovanna Castellano and Jieru Wang and Junyu Gao and Khalid Abualsaud and Laihui Ding and Lei Zhao and Marco Cianciotta and Muhammad Saqib and Noor Almaadeed and Omar Elharrouss and Pei Lyu and Qi Wang and Shidong Liu and Shuang Qiu and Siyang Pan and Somaya Al-Maadeed and Sultan Daud Khan and Tamer Khattab and Tao Han and Thomas Golda and Wei Xu and Xiang Bai and Xiaoqing Xu and Xuelong Li and Yanyun Zhao and Ye Tian and Yingnan Lin and Yongchao Xu and Yuehan Yao and Zhenyu Xu and Zhijian Zhao and Zhipeng Luo and Zhiwei Wei and Zhiyuan Zhao},
journal= {arXiv preprint arXiv:2107.08766},
year = {2021}
}
Comments
The method description of A7 Mutil-Scale Aware based SFANet (M-SFANet) is updated and missing references are added