학술논문
VisDrone-MOT2019: The Vision Meets Drone Multiple Object Tracking Challenge Results
Document Type
Conference
Author
Wen, Longyin; Zhu, Pengfei; Du, Dawei; Bian, Xiao; Ling, Haibin; Hu, Qinghua; Zheng, Jiayu; Peng, Tao; Wang, Xinyao; Zhang, Yue; Bo, Liefeng; Shi, Hailin; Zhu, Rui; Jadhav, Ajit; Dong, Bing; Lall, Brejesh; Liu, Chang; Zhang, Chunhui; Wang, Dong; Ni, Feng; Bunyak, Filiz; Wang, Gaoang; Liu, Guizhong; Seetharaman, Guna; Li, Guorong; Ardo, Hakan; Zhang, Haotian; Yu, Hongyang; Lu, Huchuan; Hwang, Jenq-Neng; Mu, Jiatong; Hu, Jinrong; Palaniappan, Kannappan; Chen, Long; Ding, Lu; Lauer, Martin; Nilsson, Mikael; Al-Shakarji, Noor M.; Mukherjee, Prerana; Huang, Qingming; Laganiere, Robert; Chen, Shuhao; Pan, Siyang; Kaushik, Vinay; Shi, Wei; Tian, Wei; Li, Weiqiang; Chen, Xin; Zhang, Xinyu; Zhang, Yanting; Zhao, Yanyun; Wang, Yong; Song, Yuduo; Yao, Yuehan; Chen, Zhaotang; Xu, Zhenyu; Xiao, Zhibin; Tong, Zhihang; Luo, Zhipeng; Sun, Zhuojin
Source
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) ICCVW Computer Vision Workshop (ICCVW), 2019 IEEE/CVF International Conference on. :189-198 Oct, 2019
Subject
Language
ISSN
2473-9944
Abstract
The Vision Meets Drone Multiple Object Tracking (MOT) Challenge 2019 is the second annual activity focusing on evaluating multi-object tracking algorithms on drones, held in conjunction with the 17-th International Conference on Computer Vision (ICCV 2019). Results of 12 submitted MOT algorithms on the collected drone-based dataset are presented. Meanwhile, we also report the results of 6 state-of-the-art MOT algorithms, and provide a comprehensive analysis and discussion of the results. The results of all submissions are publicly available at the website: http://www.aiskyeye.com/. The challenge results show that MOT on drones is far from being solved. We believe the challenge can largely boost the research and development in MOT on drone platforms.