Panoptic Perception

Panoptic perception aims to create a comprehensive, unified understanding of a scene by integrating multiple perception tasks, such as semantic segmentation, instance segmentation, and object detection, into a single framework. Current research focuses on developing robust models, often employing neural radiance fields, transformers, and multi-modal fusion (e.g., combining vision and radar data), to address challenges like handling diverse object scales and ambiguous boundaries, particularly in complex environments like autonomous driving and remote sensing. This integrated approach promises significant advancements in various fields, improving the accuracy and efficiency of scene understanding for applications ranging from robotics and autonomous vehicles to remote sensing image interpretation.