Panoptic Mapping

Panoptic mapping aims to create comprehensive 3D scene representations that integrate both semantic (e.g., "road," "building") and instance ("car 1," "building 2") information, enabling detailed scene understanding. Current research focuses on improving the accuracy and efficiency of these maps, often employing neural radiance fields, LiDAR integration, and deep learning models like Panoptic-FPN, while addressing challenges such as dynamic objects and handling uncertainty in perception. This technology is crucial for applications like autonomous navigation, robotics, and remote sensing, offering significant advancements in environmental modeling and scene interpretation.