Overhead Object Detection

Overhead object detection focuses on identifying objects within aerial or satellite imagery, aiming for accurate and efficient algorithms. Current research explores streamlined labeling techniques, such as using only centerpoints instead of full bounding boxes, and investigates the effectiveness of different data sources, including event cameras and their integration with traditional RGB imagery, often leveraging attention mechanisms to improve performance when combining ground-level and overhead views. These advancements have implications for various applications, including environmental monitoring, urban planning, and security, while also contributing to a deeper understanding of the robustness and vulnerabilities of object detection models to adversarial attacks in real-world scenarios.