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

TL;DR

This paper summarizes the 3rd Anti-UAV Workshop & Challenge, highlighting new dataset releases, the introduction of two competition tracks, and top-performing methods for multi-scale UAV object tracking and detection.

Contribution

It introduces an expanded dataset with a training set and two new challenge tracks, fostering research in UAV detection and tracking.

Findings

76 teams participated globally.

Top methods achieved significant accuracy improvements.

Benchmark dataset and results are publicly available.

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/.