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 Type | Paper |
| Authors | 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, 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 Title | Proceedings of European Conference on Computer Vision 2018 Workshops |
| Journal Citation | 11133, pp. 469-495 |
| Number of Pages | 27 |
| Year | 2019 |
| Publisher | Springer |
| Place of Publication | Germany |
| ISBN | 9783030110208 |
| 9783030110215 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-030-11021-5_28 |
| Web Address (URL) of Paper | https://link.springer.com/chapter/10.1007/978-3-030-11021-5_28 |
| Web Address (URL) of Conference Proceedings | https://link.springer.com/book/10.1007/978-3-030-11021-5 |
| Conference/Event | European 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. |
| Keywords | Performance evaluation; Drone; Single-object tracking |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 4603. 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. |
| Series | Lecture Notes in Computer Science |
| Byline Affiliations | JD 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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