BuckTales: A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes

Understanding animal behaviour is central to predicting, understanding, and miti-gating impacts of natural and anthropogenic changes on animal populations andecosystems. However, the challenges of acquiring and processing long-term, eco-logically relevant data in wild settings have constrained the scope of behaviouralresearch. The increasing availability of Unmanned Aerial Vehicles (UAVs), cou-pled with advances in machine learning, has opened new opportunities for wildlifemonitoring using aerial tracking. However, the limited availability of datasets with wildanimals in natural habitats has hindered progress in automated computer visionsolutions for long-term animal tracking. Here, we introduce the first large-scaleUAV dataset designed to solve multi-object tracking (MOT) and re-identification(Re-ID) problem in wild animals, specifically the mating behaviour (or lekking) ofblackbuck antelopes. Collected in collaboration with biologists, the MOT datasetincludes over 1.2 million annotations including 680 tracks across 12 high-resolution(5.4K)