ATLANTA — New research has been published at NeurIPS 2024. The research titled “UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles” was co-authored by Georgia State University (GSU) and TCV Alum Hui Ye, GSU Professor and Associate Chair of the Department of Computer Science, and TCV Faculty, Dr. Rajshekhar Sunderraman and Associate Professor in the School of Computing at University of Connecticut (UConn), Dr. Jonathan Shihao Ji. The research is scheduled to be presented at NeurIPS 2024, one of the top conferences in artificial intelligence, on December 12th.
Abstract
Unmanned Aerial Vehicles (UAVs), equipped with cameras, are employed in numerous applications, including aerial photography, surveillance, and agriculture. In these applications, robust object detection and tracking are essential for the effective deployment of UAVs. However, existing benchmarks for UAV applications are mainly designed for traditional 2D perception tasks, restricting the development of real-world applications that require a 3D understanding of the environment. Furthermore, despite recent advancements in single-UAV perception, limited views of a single UAV platform significantly constrain its perception capabilities over long distances or in occluded areas. To address these challenges, we introduce UAV3D, a benchmark designed to advance research in both 3D and collaborative 3D perception tasks with UAVs. UAV3D comprises 1,000 scenes, each of which has 20 frames with fully annotated 3D bounding boxes on vehicles. We provide the benchmark for four 3D perception tasks: single-UAV 3D object detection, single-UAV object tracking, collaborative-UAV 3D object detection, and collaborative-UAV object tracking. Our dataset and code are available at this https URL.
NeurIPS 2024 is the 38th Annual Conference on Neural Information Processing Systems will be held in Vancouver Convention Center, Tuesday Dec 10 through Sunday Dec 15. NeurlPS is now a multi-track interdisciplinary annual meeting that includes invited talks, demonstrations, symposia, and oral and poster presentations of refereed papers. Along with the conference is a professional exposition focusing on machine learning in practice, a series of tutorials, and topical workshops that provide a less formal setting for the exchange of ideas.