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VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results

: Fan, H.; Du, D.; Wen, L.; Zhu, P.; Hu, Q.; Ling, H.; Shah, M.; Pan, J.; Schumann, A.; Dong, B.; Stadler, D.; Xu, D.; Bunyak, F.; Seetharaman, G.; Liu, G.; Haritha, V.; Hrishikesh, P.S.; Han, J.; Palaniappan, K.; Zhu, K.; Sommer, L.W.; Zhang, L.; Shine, L.; Yao, M.; Al-Shakarji, N.M.; Li, S.; Sun, T.; Sai, W.; Yu, W.; Wu, X.; Hong, X.; Wei, X.; Zhao, X.; Zhao, Y.; Gong, Y.; Yao, Y.; He, Y.; Zhao, Z.; Xie, Z.; Yang, Z.; Xu, Z.; Luo, Z.; Duan, Z.


Bartoli, Adrien (Ed.):
Computer Vision - ECCV 2020 Workshops. Proceedings. Pt.IV : Glasgow, UK, August 23-28, 2020
Cham: Springer Nature, 2020 (Lecture Notes in Computer Science 12538)
ISBN: 978-3-030-66822-8 (Print)
ISBN: 978-3-030-66823-5 (Online)
ISBN: 978-3-030-66824-2
European Conference on Computer Vision (ECCV) <16, 2020, Online>
Computer Vision for UAVs Workshop and Challenge <2020, Online>
Conference Paper
Fraunhofer IOSB ()

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 By holding VisDrone-MOT2020 challenge, we hope to facilitate future research and applications of MOT algorithms on drone videos.