Animal Tracking

Animal tracking research focuses on automatically identifying, locating, and analyzing animal movements and behaviors from various data sources, primarily images and videos. Current efforts concentrate on developing robust algorithms and models, such as those based on transformer networks and instance segmentation, to handle challenges like multi-animal tracking, pose estimation, and species identification, often leveraging large-scale datasets and semi-supervised learning techniques. These advancements are crucial for improving wildlife monitoring, understanding animal behavior in ecological and biological studies, and facilitating more efficient conservation efforts. The development of publicly available datasets and standardized evaluation benchmarks is driving progress in the field.