AI RESEARCH
LiPS: Lightweight Panoptic Segmentation for Resource-Constrained Robotics
arXiv CS.CV
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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