AI RESEARCH

LiPS: Lightweight Panoptic Segmentation for Resource-Constrained Robotics

arXiv CS.CV

ArXi:2604.00634v1 Announce Type: cross Panoptic segmentation is a key enabler for robotic perception, as it unifies semantic understanding with object-level reasoning. However, the increasing complexity of state-of-the-art models makes them unsuitable for deployment on resource-constrained platforms such as mobile robots. We propose a novel approach called LiPS that addresses the challenge of efficient-to-compute panoptic segmentation with a lightweight design that retains query-based decoding while