The 3rd Anti-UAV Workshop & Challenge: Methods and Results

• URL: http://arxiv.org/abs/2305.07290v1
• Date: Fri, 12 May 2023 07:37:04 GMT
• Title: The 3rd Anti-UAV Workshop & Challenge: Methods and Results
• Authors: Jian Zhao, Jianan Li, Lei Jin, Jiaming Chu, Zhihao Zhang, Jun Wang, Jiangqiang Xia, Kai Wang, Yang Liu, Sadaf Gulshad, Jiaojiao Zhao, Tianyang Xu, Xuefeng Zhu, Shihan Liu, Zheng Zhu, Guibo Zhu, Zechao Li, Zheng Wang, Baigui Sun, Yandong Guo, Shin ichi Satoh, Junliang Xing, Jane Shen Shengmei
• Abstract summary: The 3rd Anti-UAV Workshop & Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UAV Challenge has been publicly released.
• Score: 65.9405033602133
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The 3rd Anti-UAV Workshop & Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UAV Challenge has been publicly released. There are two main differences between this year's competition and the previous two. First, we have expanded the existing dataset, and for the first time, released a training set so that participants can focus on improving their models. Second, we set up two tracks for the first time, i.e., Anti-UAV Tracking and Anti-UAV Detection & Tracking. Around 76 participating teams from the globe competed in the 3rd Anti-UAV Challenge. In this paper, we provide a brief summary of the 3rd Anti-UAV Workshop & Challenge including brief introductions to the top three methods in each track. The submission leaderboard will be reopened for researchers that are interested in the Anti-UAV challenge. The benchmark dataset and other information can be found at: https://anti-uav.github.io/.

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