The First Competition on Resource-Limited Infrared Small Target Detection Challenge: Methods and Results
This competition addresses the problem of deploying infrared small target detection technology under resource constraints, which is incremental as it builds on existing detection methods by focusing on efficiency and limited supervision.
The paper summarizes the first competition on resource-limited infrared small target detection (LimitIRSTD), which included weakly-supervised and lightweight detection tracks, with 46 and 60 teams participating, respectively, and describes the top-performing methods and their results.
In this paper, we briefly summarize the first competition on resource-limited infrared small target detection (namely, LimitIRSTD). This competition has two tracks, including weakly-supervised infrared small target detection (Track 1) and lightweight infrared small target detection (Track 2). 46 and 60 teams successfully registered and took part in Tracks 1 and Track 2, respectively. The top-performing methods and their results in each track are described with details. This competition inspires the community to explore the tough problems in the application of infrared small target detection, and ultimately promote the deployment of this technology under limited resource.