The 3rd Anti-UAV Workshop & Challenge: Methods and Results
This work addresses the need for improved UAV tracking methods in security and surveillance domains, but it is incremental as it builds on previous challenges by adding a training set and new tracks.
The paper describes the 3rd Anti-UAV Workshop & Challenge, which tackled the problem of multi-scale object tracking for unmanned aerial vehicles (UAVs) by expanding a public dataset and introducing two competition tracks, with around 76 teams participating globally.
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/.