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

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 Duan

doi:10.1007/978-3-030-66823-5_43

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

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 Duan

^*Corresponding author for this work

Stony Brook University
Kitware, Inc
JD Finance America Corporation
Tianjin University
University of Central Florida
Fraunhofer Center for Machine Learning
DeepBlue Technology (Shanghai)
Karlsruhe Institute of Technology
Zhejiang University
University of Missouri
Naval Research Laboratory
Xi'an Jiaotong University
College of Engineering Trivandrum
Xidian University
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation
CAS - Institute of Software
University of Technology- Iraq
Beijing University of Posts and Telecommunications
Southwestern University of Finance and Economics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

21 Scopus citations

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.

Original language	English
Title of host publication	Computer Vision – ECCV 2020 Workshops, Proceedings
Editors	Adrien Bartoli, Andrea Fusiello
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	713-727
Number of pages	15
ISBN (Print)	9783030668228
DOIs	https://doi.org/10.1007/978-3-030-66823-5_43
State	Published - 2020
Externally published	Yes
Event	Workshops held at the 16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom Duration: 23 Aug 2020 → 28 Aug 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12538 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Workshops held at the 16th European Conference on Computer Vision, ECCV 2020
Country/Territory	United Kingdom
City	Glasgow
Period	23/08/20 → 28/08/20

Keywords

Drone
Drone-based multiple object tracking
Performance evaluation

Access to Document

10.1007/978-3-030-66823-5_43

Cite this

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., ... Duan, Z. (2020). VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results. In A. Bartoli, & A. Fusiello (Eds.), Computer Vision – ECCV 2020 Workshops, Proceedings (pp. 713-727). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12538 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-66823-5_43

Fan, Heng ; Du, Dawei ; Wen, Longyin et al. / VisDrone-MOT2020 : The Vision Meets Drone Multiple Object Tracking Challenge Results. Computer Vision – ECCV 2020 Workshops, Proceedings. editor / Adrien Bartoli ; Andrea Fusiello. Springer Science and Business Media Deutschland GmbH, 2020. pp. 713-727 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{7e8a599a8c0243df95873d4e320b844a,

title = "VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results",

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.",

keywords = "Drone, Drone-based multiple object tracking, Performance evaluation",

author = "Heng Fan and Dawei Du and Longyin Wen and Pengfei Zhu and Qinghua Hu and Haibin Ling and Mubarak Shah and Junwen Pan and Arne Schumann and Bin Dong and Daniel Stadler and Duo Xu and Filiz Bunyak and Guna Seetharaman and Guizhong Liu and V. Haritha and Hrishikesh, \{P. S.\} and Jie Han and Kannappan Palaniappan and Kaojin Zhu and Sommer, \{Lars Wilko\} and Libo Zhang and Linu Shine and Min Yao and Al-Shakarji, \{Noor M.\} and Shengwen Li and Ting Sun and Wang Sai and Wentao Yu and Xi Wu and Xiaopeng Hong and Xing Wei and Xingjie Zhao and Yanyun Zhao and Yihong Gong and Yuehan Yao and Yuhang He and Zhaoze Zhao and Zhen Xie and Zheng Yang and Zhenyu Xu and Zhipeng Luo and Zhizhao Duan",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; Workshops held at the 16th European Conference on Computer Vision, ECCV 2020 ; Conference date: 23-08-2020 Through 28-08-2020",

year = "2020",

doi = "10.1007/978-3-030-66823-5\_43",

language = "英语",

isbn = "9783030668228",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "713--727",

editor = "Adrien Bartoli and Andrea Fusiello",

booktitle = "Computer Vision – ECCV 2020 Workshops, Proceedings",

address = "德国",

}

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, PS, Han, J, Palaniappan, K, Zhu, K, Sommer, LW, Zhang, L, Shine, L, Yao, M, Al-Shakarji, NM, 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 2020, VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results. in A Bartoli & A Fusiello (eds), Computer Vision – ECCV 2020 Workshops, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12538 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 713-727, Workshops held at the 16th European Conference on Computer Vision, ECCV 2020, Glasgow, United Kingdom, 23/08/20. https://doi.org/10.1007/978-3-030-66823-5_43

VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results. / Fan, Heng; Du, Dawei; Wen, Longyin et al.
Computer Vision – ECCV 2020 Workshops, Proceedings. ed. / Adrien Bartoli; Andrea Fusiello. Springer Science and Business Media Deutschland GmbH, 2020. p. 713-727 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12538 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - VisDrone-MOT2020

T2 - Workshops held at the 16th European Conference on Computer Vision, ECCV 2020

AU - Fan, Heng

AU - Du, Dawei

AU - Wen, Longyin

AU - Zhu, Pengfei

AU - Hu, Qinghua

AU - Ling, Haibin

AU - Shah, Mubarak

AU - Pan, Junwen

AU - Schumann, Arne

AU - Dong, Bin

AU - Stadler, Daniel

AU - Xu, Duo

AU - Bunyak, Filiz

AU - Seetharaman, Guna

AU - Liu, Guizhong

AU - Haritha, V.

AU - Hrishikesh, P. S.

AU - Han, Jie

AU - Palaniappan, Kannappan

AU - Zhu, Kaojin

AU - Sommer, Lars Wilko

AU - Zhang, Libo

AU - Shine, Linu

AU - Yao, Min

AU - Al-Shakarji, Noor M.

AU - Li, Shengwen

AU - Sun, Ting

AU - Sai, Wang

AU - Yu, Wentao

AU - Wu, Xi

AU - Hong, Xiaopeng

AU - Wei, Xing

AU - Zhao, Xingjie

AU - Zhao, Yanyun

AU - Gong, Yihong

AU - Yao, Yuehan

AU - He, Yuhang

AU - Zhao, Zhaoze

AU - Xie, Zhen

AU - Yang, Zheng

AU - Xu, Zhenyu

AU - Luo, Zhipeng

AU - Duan, Zhizhao

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Drone

KW - Drone-based multiple object tracking

KW - Performance evaluation

UR - https://www.scopus.com/pages/publications/85101770013

U2 - 10.1007/978-3-030-66823-5_43

DO - 10.1007/978-3-030-66823-5_43

M3 - 会议稿件

AN - SCOPUS:85101770013

SN - 9783030668228

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 713

EP - 727

BT - Computer Vision – ECCV 2020 Workshops, Proceedings

A2 - Bartoli, Adrien

A2 - Fusiello, Andrea

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 23 August 2020 through 28 August 2020

ER -

Fan H, Du D, Wen L, Zhu P, Hu Q, Ling H et al. VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results. In Bartoli A, Fusiello A, editors, Computer Vision – ECCV 2020 Workshops, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 713-727. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-66823-5_43

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

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