VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results
Authors: 
Heng Fan, Dawei Du, Longyin Wen, Pengfei Zhu, Qinghua Hu, Haibin Ling, Mubarak Shah, Junwen Pan, Arne Schumann, Bin Dong, Daniel Stadler, Duo Xu, Filiz Bunyak, Guna Seetharaman, Guizhong Liu, V. Haritha, P. S. Hrishikesh, Jie Han, Kannappan Palaniappan, Kaojin Zhu, Lars Wilko Sommer, Libo Zhang, Linu Shine, Min Yao, Noor M. Al-Shakarji, Shengwen Li, Ting Sun, Wang Sai, Wentao Yu, Xi Wu, Xiaopeng Hong, Xing Wei, Xingjie Zhao, Yanyun Zhao, Yihong Gong, Yuehan Yao, Yuhang He, Zhaoze Zhao, Zhen Xie, Zheng Yang, Zhenyu Xu, Zhipeng Luo, Zhizhao DuanAuthors Info & Claims
Pages 713 - 727
Abstract
The Vision Meets Drone (VisDrone2020) Multiple Object Tracking (MOT) is the third annual UAV MOT tracking evaluation activity organized by the VisDrone team, in conjunction with European Conference on Computer Vision (ECCV 2020). The VisDrone-MOT2020 consists of 79 challenging video sequences, including 56 videos (24K frames) for training, 7 videos (3K frames) for validation and 17 videos (6K frames) for evaluation. All frames in these sequences are manually annotated with high-quality bounding boxes. Results of 12 participating MOT algorithms are presented and analyzed in detail. The challenging results, video sequences as well as the evaluation toolkit are made available at http://aiskyeye.com/. By holding VisDrone-MOT2020 challenge, we hope to facilitate future research and applications of MOT algorithms on drone videos.
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Published In
Aug 2020
776 pages
© Springer Nature Switzerland AG 2020.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 23 August 2020
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