VisDrone-SOT2020: The Vision Meets Drone Single Object Tracking Challenge Results

Heng Fan; Longyin Wen; Dawei Du; Pengfei Zhu; Qinghua Hu; Haibin Ling; Mubarak Shah; Biao Wang; Bin Dong; Di Yuan; Dong Wang; Dongjie Zhou; Haoyang Sun; Hossein Ghanei-Yakhdan; Huchuan Lu; Javad Khaghani; Jinghao Zhou; Keyang Wang; Lei Pang; Lei Zhang; Li Cheng; Liting Lin; Lu Ding; Nana Fan; Peng Wang; Penghao Zhang; Ruiyan Ma; Seyed Mojtaba Marvasti-Zadeh; Shohreh Kasaei; Shuhao Chen; Simiao Lai; Tianyang Xu; Wentao He; Xiaojun Wu; Xin Hou; Xuefeng Zhu; Yanjie Gao; Yanyun Zhao; Yong Wang; Yong Xu; Yubo Sun; Yuting Yang; Yuxuan Li; Zezhou Wang; Zhenwei He; Zhenyu He; Zhipeng Luo; Zhongjian Huang; Zhongzhou Zhang; Zikai Zhang; Zitong Yi

doi:10.1007/978-3-030-66823-5_44

VisDrone-SOT2020: The Vision Meets Drone Single Object Tracking Challenge Results

Heng Fan
, Longyin Wen
, Dawei Du
, Pengfei Zhu^*
, Qinghua Hu
, Haibin Ling
, Mubarak Shah
, Biao Wang
, Bin Dong
, Di Yuan
, Dong Wang
, Dongjie Zhou
, Haoyang Sun
, Hossein Ghanei-Yakhdan
, Huchuan Lu
, Javad Khaghani
, Jinghao Zhou
, Keyang Wang
, Lei Pang
, Lei Zhang

Li Cheng, Liting Lin, Lu Ding, Nana Fan, Peng Wang, Penghao Zhang, Ruiyan Ma, Seyed Mojtaba Marvasti-Zadeh, Shohreh Kasaei, Shuhao Chen, Simiao Lai, Tianyang Xu, Wentao He, Xiaojun Wu, Xin Hou, Xuefeng Zhu, Yanjie Gao, Yanyun Zhao, Yong Wang, Yong Xu, Yubo Sun, Yuting Yang, Yuxuan Li, Zezhou Wang, Zhenwei He, Zhenyu He, Zhipeng Luo, Zhongjian Huang, Zhongzhou Zhang, Zikai Zhang, Zitong Yi

^*Corresponding author for this work

Stony Brook University
JD Finance America Corporation
Kitware, Inc
Tianjin University
University of Central Florida
WeBank
DeepBlue Technology
Harbin Institute of Technology Shenzhen
Dalian University of Technology
Beijing Institute of Remote Sensing Equipment
Northwestern Polytechnical University Xian
Yazd University
University of Alberta
Chongqing University
Chinese Academy of Sciences
South China University of Technology
Shanghai Jiao Tong University
Xidian University
Sharif University of Technology
University of Surrey
Jiangnan University
Beijing University of Posts and Telecommunications
Sun Yat-Sen University
DeepBlue Technology (Shanghai)

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

25 Scopus citations

Abstract

The Vision Meets Drone (VisDrone2020) Single Object Tracking is the third annual UAV tracking evaluation activity organized by the VisDrone team, in conjunction with European Conference on Computer Vision (ECCV 2020). The VisDrone-SOT2020 Challenge presents and discusses the results of 13 participating algorithms in detail. By using ensemble of different trackers trained on several large-scale datasets, the top performer in VisDrone-SOT2020 achieves better results than the counterparts in VisDrone-SOT2018 and VisDrone-SOT2019. The challenging results, collected videos as well as the valuation toolkit are made available at http://aiskyeye.com/. By holding VisDrone-SOT2020 challenge, we hope to provide the community a dedicated platform for developing and evaluating drone-based tracking approaches.

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	728-749
Number of pages	22
ISBN (Print)	9783030668228
DOIs	https://doi.org/10.1007/978-3-030-66823-5_44
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 single object tracking
Performance evaluation

Access to Document

10.1007/978-3-030-66823-5_44

Cite this

Fan, H., Wen, L., Du, D., Zhu, P., Hu, Q., Ling, H., Shah, M., Wang, B., Dong, B., Yuan, D., Wang, D., Zhou, D., Sun, H., Ghanei-Yakhdan, H., Lu, H., Khaghani, J., Zhou, J., Wang, K., Pang, L., ... Yi, Z. (2020). VisDrone-SOT2020: The Vision Meets Drone Single Object Tracking Challenge Results. In A. Bartoli, & A. Fusiello (Eds.), Computer Vision – ECCV 2020 Workshops, Proceedings (pp. 728-749). (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_44

Fan, Heng ; Wen, Longyin ; Du, Dawei et al. / VisDrone-SOT2020 : The Vision Meets Drone Single Object Tracking Challenge Results. Computer Vision – ECCV 2020 Workshops, Proceedings. editor / Adrien Bartoli ; Andrea Fusiello. Springer Science and Business Media Deutschland GmbH, 2020. pp. 728-749 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{49cd13f8ea66409b8c125b43243f8535,

title = "VisDrone-SOT2020: The Vision Meets Drone Single Object Tracking Challenge Results",

abstract = "The Vision Meets Drone (VisDrone2020) Single Object Tracking is the third annual UAV tracking evaluation activity organized by the VisDrone team, in conjunction with European Conference on Computer Vision (ECCV 2020). The VisDrone-SOT2020 Challenge presents and discusses the results of 13 participating algorithms in detail. By using ensemble of different trackers trained on several large-scale datasets, the top performer in VisDrone-SOT2020 achieves better results than the counterparts in VisDrone-SOT2018 and VisDrone-SOT2019. The challenging results, collected videos as well as the valuation toolkit are made available at http://aiskyeye.com/. By holding VisDrone-SOT2020 challenge, we hope to provide the community a dedicated platform for developing and evaluating drone-based tracking approaches.",

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

author = "Heng Fan and Longyin Wen and Dawei Du and Pengfei Zhu and Qinghua Hu and Haibin Ling and Mubarak Shah and Biao Wang and Bin Dong and Di Yuan and Dong Wang and Dongjie Zhou and Haoyang Sun and Hossein Ghanei-Yakhdan and Huchuan Lu and Javad Khaghani and Jinghao Zhou and Keyang Wang and Lei Pang and Lei Zhang and Li Cheng and Liting Lin and Lu Ding and Nana Fan and Peng Wang and Penghao Zhang and Ruiyan Ma and Marvasti-Zadeh, \{Seyed Mojtaba\} and Shohreh Kasaei and Shuhao Chen and Simiao Lai and Tianyang Xu and Wentao He and Xiaojun Wu and Xin Hou and Xuefeng Zhu and Yanjie Gao and Yanyun Zhao and Yong Wang and Yong Xu and Yubo Sun and Yuting Yang and Yuxuan Li and Zezhou Wang and Zhenwei He and Zhenyu He and Zhipeng Luo and Zhongjian Huang and Zhongzhou Zhang and Zikai Zhang and Zitong Yi",

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\_44",

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 = "728--749",

editor = "Adrien Bartoli and Andrea Fusiello",

booktitle = "Computer Vision {\textendash} ECCV 2020 Workshops, Proceedings",

address = "德国",

}

Fan, H, Wen, L, Du, D, Zhu, P, Hu, Q, Ling, H, Shah, M, Wang, B, Dong, B, Yuan, D, Wang, D, Zhou, D, Sun, H, Ghanei-Yakhdan, H, Lu, H, Khaghani, J, Zhou, J, Wang, K, Pang, L, Zhang, L, Cheng, L, Lin, L, Ding, L, Fan, N, Wang, P, Zhang, P, Ma, R, Marvasti-Zadeh, SM, Kasaei, S, Chen, S, Lai, S, Xu, T, He, W, Wu, X, Hou, X, Zhu, X, Gao, Y, Zhao, Y, Wang, Y, Xu, Y, Sun, Y, Yang, Y, Li, Y, Wang, Z, He, Z, He, Z, Luo, Z, Huang, Z, Zhang, Z, Zhang, Z & Yi, Z 2020, VisDrone-SOT2020: The Vision Meets Drone Single 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. 728-749, 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_44

VisDrone-SOT2020: The Vision Meets Drone Single Object Tracking Challenge Results. / Fan, Heng; Wen, Longyin; Du, Dawei et al.
Computer Vision – ECCV 2020 Workshops, Proceedings. ed. / Adrien Bartoli; Andrea Fusiello. Springer Science and Business Media Deutschland GmbH, 2020. p. 728-749 (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-SOT2020

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

AU - Fan, Heng

AU - Wen, Longyin

AU - Du, Dawei

AU - Zhu, Pengfei

AU - Hu, Qinghua

AU - Ling, Haibin

AU - Shah, Mubarak

AU - Wang, Biao

AU - Dong, Bin

AU - Yuan, Di

AU - Wang, Dong

AU - Zhou, Dongjie

AU - Sun, Haoyang

AU - Ghanei-Yakhdan, Hossein

AU - Lu, Huchuan

AU - Khaghani, Javad

AU - Zhou, Jinghao

AU - Wang, Keyang

AU - Pang, Lei

AU - Zhang, Lei

AU - Cheng, Li

AU - Lin, Liting

AU - Ding, Lu

AU - Fan, Nana

AU - Wang, Peng

AU - Zhang, Penghao

AU - Ma, Ruiyan

AU - Marvasti-Zadeh, Seyed Mojtaba

AU - Kasaei, Shohreh

AU - Chen, Shuhao

AU - Lai, Simiao

AU - Xu, Tianyang

AU - He, Wentao

AU - Wu, Xiaojun

AU - Hou, Xin

AU - Zhu, Xuefeng

AU - Gao, Yanjie

AU - Zhao, Yanyun

AU - Wang, Yong

AU - Xu, Yong

AU - Sun, Yubo

AU - Yang, Yuting

AU - Li, Yuxuan

AU - Wang, Zezhou

AU - He, Zhenwei

AU - He, Zhenyu

AU - Luo, Zhipeng

AU - Huang, Zhongjian

AU - Zhang, Zhongzhou

AU - Zhang, Zikai

AU - Yi, Zitong

PY - 2020

Y1 - 2020

N2 - The Vision Meets Drone (VisDrone2020) Single Object Tracking is the third annual UAV tracking evaluation activity organized by the VisDrone team, in conjunction with European Conference on Computer Vision (ECCV 2020). The VisDrone-SOT2020 Challenge presents and discusses the results of 13 participating algorithms in detail. By using ensemble of different trackers trained on several large-scale datasets, the top performer in VisDrone-SOT2020 achieves better results than the counterparts in VisDrone-SOT2018 and VisDrone-SOT2019. The challenging results, collected videos as well as the valuation toolkit are made available at http://aiskyeye.com/. By holding VisDrone-SOT2020 challenge, we hope to provide the community a dedicated platform for developing and evaluating drone-based tracking approaches.

AB - The Vision Meets Drone (VisDrone2020) Single Object Tracking is the third annual UAV tracking evaluation activity organized by the VisDrone team, in conjunction with European Conference on Computer Vision (ECCV 2020). The VisDrone-SOT2020 Challenge presents and discusses the results of 13 participating algorithms in detail. By using ensemble of different trackers trained on several large-scale datasets, the top performer in VisDrone-SOT2020 achieves better results than the counterparts in VisDrone-SOT2018 and VisDrone-SOT2019. The challenging results, collected videos as well as the valuation toolkit are made available at http://aiskyeye.com/. By holding VisDrone-SOT2020 challenge, we hope to provide the community a dedicated platform for developing and evaluating drone-based tracking approaches.

KW - Drone

KW - Drone-based single object tracking

KW - Performance evaluation

UR - https://www.scopus.com/pages/publications/85101750735

U2 - 10.1007/978-3-030-66823-5_44

DO - 10.1007/978-3-030-66823-5_44

M3 - 会议稿件

AN - SCOPUS:85101750735

SN - 9783030668228

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

SP - 728

EP - 749

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, Wen L, Du D, Zhu P, Hu Q, Ling H et al. VisDrone-SOT2020: The Vision Meets Drone Single 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. 728-749. (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_44

VisDrone-SOT2020: The Vision Meets Drone Single Object Tracking Challenge Results

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