The 1st Tiny Object Detection Challenge: Methods and Results

Xuehui Yu; Zhenjun Han; Yuqi Gong; Nan Jan; Jian Zhao; Qixiang Ye; Jie Chen; Yuan Feng; Bin Zhang; Xiaodi Wang; Ying Xin; Jingwei Liu; Mingyuan Mao; Sheng Xu; Baochang Zhang; Shumin Han; Cheng Gao; Wei Tang; Lizuo Jin; Mingbo Hong; Yuchao Yang; Shuiwang Li; Huan Luo; Qijun Zhao; Humphrey Shi

doi:10.1007/978-3-030-68238-5_23

The 1st Tiny Object Detection Challenge: Methods and Results

Xuehui Yu, Zhenjun Han^*, Yuqi Gong, Nan Jan, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo HongYuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi

^*Corresponding author for this work

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

22 Citations (Scopus)

Abstract

The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection. The TinyPerson dataset was used for the TOD Challenge and is publicly released. It has 1610 images and 72651 box-level annotations. Around 36 participating teams from the globe competed in the 1st TOD Challenge. In this paper, we provide a brief summary of the 1st TOD Challenge including brief introductions to the top three methods.The submission leaderboard will be reopened for researchers that are interested in the TOD challenge. The benchmark dataset and other information can be found at: https://github.com/ucas-vg/TinyBenchmark.

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	315-323
Number of pages	9
ISBN (Print)	9783030682378
DOIs	https://doi.org/10.1007/978-3-030-68238-5_23
Publication status	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	12539 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

Tiny Object Detection
Visual recognition

Access to Document

10.1007/978-3-030-68238-5_23

Cite this

Yu, X., Han, Z., Gong, Y., Jan, N., Zhao, J., Ye, Q., Chen, J., Feng, Y., Zhang, B., Wang, X., Xin, Y., Liu, J., Mao, M., Xu, S., Zhang, B., Han, S., Gao, C., Tang, W., Jin, L., ... Shi, H. (2020). The 1st Tiny Object Detection Challenge: Methods and Results. In A. Bartoli, & A. Fusiello (Eds.), Computer Vision – ECCV 2020 Workshops, Proceedings (pp. 315-323). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12539 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-68238-5_23

Yu, Xuehui ; Han, Zhenjun ; Gong, Yuqi et al. / The 1st Tiny Object Detection Challenge : Methods and Results. Computer Vision – ECCV 2020 Workshops, Proceedings. editor / Adrien Bartoli ; Andrea Fusiello. Springer Science and Business Media Deutschland GmbH, 2020. pp. 315-323 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{4b1bf3810a9c48628571a7b3b849fa4f,

title = "The 1st Tiny Object Detection Challenge: Methods and Results",

abstract = "The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection. The TinyPerson dataset was used for the TOD Challenge and is publicly released. It has 1610 images and 72651 box-level annotations. Around 36 participating teams from the globe competed in the 1st TOD Challenge. In this paper, we provide a brief summary of the 1st TOD Challenge including brief introductions to the top three methods.The submission leaderboard will be reopened for researchers that are interested in the TOD challenge. The benchmark dataset and other information can be found at: https://github.com/ucas-vg/TinyBenchmark.",

keywords = "Tiny Object Detection, Visual recognition",

author = "Xuehui Yu and Zhenjun Han and Yuqi Gong and Nan Jan and Jian Zhao and Qixiang Ye and Jie Chen and Yuan Feng and Bin Zhang and Xiaodi Wang and Ying Xin and Jingwei Liu and Mingyuan Mao and Sheng Xu and Baochang Zhang and Shumin Han and Cheng Gao and Wei Tang and Lizuo Jin and Mingbo Hong and Yuchao Yang and Shuiwang Li and Huan Luo and Qijun Zhao and Humphrey Shi",

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 = "10.1007/978-3-030-68238-5_23",

language = "English",

isbn = "9783030682378",

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

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editor = "Adrien Bartoli and Andrea Fusiello",

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

address = "Germany",

}

Yu, X, Han, Z, Gong, Y, Jan, N, Zhao, J, Ye, Q, Chen, J, Feng, Y, Zhang, B, Wang, X, Xin, Y, Liu, J, Mao, M, Xu, S, Zhang, B, Han, S, Gao, C, Tang, W, Jin, L, Hong, M, Yang, Y, Li, S, Luo, H, Zhao, Q & Shi, H 2020, The 1st Tiny Object Detection Challenge: Methods and 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. 12539 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 315-323, Workshops held at the 16th European Conference on Computer Vision, ECCV 2020, Glasgow, United Kingdom, 23/08/20. https://doi.org/10.1007/978-3-030-68238-5_23

The 1st Tiny Object Detection Challenge: Methods and Results. / Yu, Xuehui; Han, Zhenjun; Gong, Yuqi et al.
Computer Vision – ECCV 2020 Workshops, Proceedings. ed. / Adrien Bartoli; Andrea Fusiello. Springer Science and Business Media Deutschland GmbH, 2020. p. 315-323 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12539 LNCS).

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

TY - GEN

T1 - The 1st Tiny Object Detection Challenge

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

AU - Yu, Xuehui

AU - Han, Zhenjun

AU - Gong, Yuqi

AU - Jan, Nan

AU - Zhao, Jian

AU - Ye, Qixiang

AU - Chen, Jie

AU - Feng, Yuan

AU - Zhang, Bin

AU - Wang, Xiaodi

AU - Xin, Ying

AU - Liu, Jingwei

AU - Mao, Mingyuan

AU - Xu, Sheng

AU - Zhang, Baochang

AU - Han, Shumin

AU - Gao, Cheng

AU - Tang, Wei

AU - Jin, Lizuo

AU - Hong, Mingbo

AU - Yang, Yuchao

AU - Li, Shuiwang

AU - Luo, Huan

AU - Zhao, Qijun

AU - Shi, Humphrey

PY - 2020

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AB - The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection. The TinyPerson dataset was used for the TOD Challenge and is publicly released. It has 1610 images and 72651 box-level annotations. Around 36 participating teams from the globe competed in the 1st TOD Challenge. In this paper, we provide a brief summary of the 1st TOD Challenge including brief introductions to the top three methods.The submission leaderboard will be reopened for researchers that are interested in the TOD challenge. The benchmark dataset and other information can be found at: https://github.com/ucas-vg/TinyBenchmark.

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DO - 10.1007/978-3-030-68238-5_23

M3 - Conference contribution

AN - SCOPUS:85101301894

SN - 9783030682378

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

SP - 315

EP - 323

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 -

Yu X, Han Z, Gong Y, Jan N, Zhao J, Ye Q et al. The 1st Tiny Object Detection Challenge: Methods and Results. In Bartoli A, Fusiello A, editors, Computer Vision – ECCV 2020 Workshops, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 315-323. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-68238-5_23

The 1st Tiny Object Detection Challenge: Methods and Results

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