Visdrone-sot2018: The vision meets drone single-object tracking challenge results

Paper


Wen, Longyin, Zhu, Pengfei, Du, Dawei, Bian, Xiao, Ling, Haibin, Hu, Qinghua, Liu, Chenfeng, Cheng, Hao, Liu, Xiaoyu, Ma, Wenya, Nie, Qinqin, Wu, Haotian, Wang, Lianjie, Perera, Asanka G., Zhang, Baochang, Heo, Byeongho, Liu, Chunlei, Li, Dongdong, Michail, Emmanouil, ..., He, Zhiqun. 2019. "Visdrone-sot2018: The vision meets drone single-object tracking challenge results." European Conference on Computer Vision 2018 Workshops. Munich, Germany 09 - 14 Sep 2018 Germany. Springer. https://doi.org/10.1007/978-3-030-11021-5_28
Paper/Presentation Title

Visdrone-sot2018: The vision meets drone single-object tracking challenge results

Presentation TypePaper
AuthorsWen, Longyin, Zhu, Pengfei, Du, Dawei, Bian, Xiao, Ling, Haibin, Hu, Qinghua, Liu, Chenfeng, Cheng, Hao, Liu, Xiaoyu, Ma, Wenya, Nie, Qinqin, Wu, Haotian, Wang, Lianjie, Perera, Asanka G., Zhang, Baochang, Heo, Byeongho, Liu, Chunlei, Li, Dongdong, Michail, Emmanouil, Chen, Hanlin, Liu, Hao, Li, Haojie, Kompatsiaris, Ioannis, Cheng, Jian, Fan, Jiaqing, Zhang, Jie, Choi, Jin Young, Li, Jing, Yang, Jinyu, Choi, Jongwon, Zhao, Juanping, Han, Jungong, Zhang, Kaihua, Duan, Kaiwen, Song, Ke, Avgerinakis, Konstantinos, Lee, Kyuewang, Ding, Lu, Lauer, Martin, Giannakeris, Panagiotis, Zhang, Peizhen, Wang, Qiang, Xu, Qianqian, Huang, Qingming, Liu, Qingshan, Laganière, Robert, Zhang, Ruixin, Yun, Sangdoo, Zhu, Shengyin, Wu, Sihang, Vrochidis, Stefanos, Tian, Wei, Zhang, Wei, Chen, Weidong, Hu, Weiming, Wang, Wenhao, Zhang, Wenhua, Ding, Wenrui, He, Xiaohao, Li, Xiaotong, Zhang, Xin, Luo, Xinbin, Hu, Xixi, Meng, Yang, Kuai, Yangliu, Zhao, Yanyun, Li, Yaxuan, Yang, Yifan, Zhang, Yifan, Wang, Yong, Qi, Yuankai, Deng, Zhipeng and He, Zhiqun
Journal or Proceedings TitleProceedings of European Conference on Computer Vision 2018 Workshops
Journal Citation11133, pp. 469-495
Number of Pages27
Year2019
PublisherSpringer
Place of PublicationGermany
ISBN9783030110208
9783030110215
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-030-11021-5_28
Web Address (URL) of Paperhttps://link.springer.com/chapter/10.1007/978-3-030-11021-5_28
Web Address (URL) of Conference Proceedingshttps://link.springer.com/book/10.1007/978-3-030-11021-5
Conference/EventEuropean Conference on Computer Vision 2018 Workshops
Event Details
European Conference on Computer Vision 2018 Workshops
Computer Vision – ECCV 2018 Workshops
Parent
European Conference on Computer Vision
Delivery
In person
Event Date
09 to end of 14 Sep 2018
Event Location
Munich, Germany
Abstract

Single-object tracking, also known as visual tracking, on the drone platform attracts much attention recently with various applications in computer vision, such as filming and surveillance. However, the lack of commonly accepted annotated datasets and standard evaluation platform prevent the developments of algorithms. To address this issue, the Vision Meets Drone Single-Object Tracking (VisDrone-SOT2018) Challenge workshop was organized in conjunction with the 15th European Conference on Computer Vision (ECCV 2018) to track and advance the technologies in such field. Specifically, we collect a dataset, including 132 video sequences divided into three non-overlapping sets, i.e., training (86 sequences with 69, 941 frames), validation (11 sequences with 7, 046 frames), and testing (35 sequences with 29, 367 frames) sets. We provide fully annotated bounding boxes of the targets as well as several useful attributes, e.g., occlusion, background clutter, and camera motion. The tracking targets in these sequences include pedestrians, cars, buses, and animals. The dataset is extremely challenging due to various factors, such as occlusion, large scale, pose variation, and fast motion. We present the evaluation protocol of the VisDrone-SOT2018 challenge and the results of a comparison of 22 trackers on the benchmark dataset, which are publicly available on the challenge website: http://www.aiskyeye.com/. We hope this challenge largely boosts the research and development in single object tracking on drone platforms.

KeywordsPerformance evaluation; Drone; Single-object tracking
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 20204603. Computer vision and multimedia computation
Public Notes

The accessible file is the accepted version of the paper. Please refer to the URL for the published version.

SeriesLecture Notes in Computer Science
Byline AffiliationsJD Finance, United States
Tianjin University, China
University at Albany, United States
GE Global Research, United States
Temple University, United States
University of Southern Queensland
Beihang University, China
Seoul National University, Korea
National University of Defense Technology, China
Centre for Research & Technology Hellas, Greece
Shenyang Aerospace University, China
South China University of Technology, China
Chinese Academy of Sciences, China
Shandong University, China
Civil Aviation University of China, China
Samsung R&D Campus, South Korea
Shanghai Jiao Tong University, China
Lancaster University, United Kingdom
Nanjing University of Information Science and Technology, China
University of Chinese Academy of Sciences, China
Karlsruhe Institute of Technology, Germany
Sun Yat-sen University, China
Harbin Institute of Technology, China
University of Ottawa, Canada
Tencent, China
NAVER Corp, South Korea
Beijing University of Posts and Telecommunications, China
Xidian University, China
Tsinghua University, China
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