Aerial Object Detection

Aerial object detection focuses on automatically identifying and locating objects within aerial imagery, primarily from drones and satellites, aiming for accurate and efficient performance. Current research emphasizes improving detection of small, densely packed, or oddly oriented objects, often leveraging advancements in YOLO-based architectures, transformers, and other deep learning models, along with techniques like super-resolution and multi-modal fusion. This field is crucial for numerous applications, including autonomous navigation, environmental monitoring, and urban planning, driving advancements in both computer vision algorithms and real-world deployment on resource-constrained platforms like UAVs.