SOURCE-LINKED INTELLIGENCE
Beyond Relative Geometry: Metric-Aware Geometry Perception for Robotics
Recent embodied models increasingly leverage geometric representations to improve spatial reasoning and robotic manipulation. However, existing reconstruction methods only reconstruct relative geometry with arbitrary scales, causing predicted object dimensions and spatial distances to vary across scenes, viewpoints, and input configurations. This inconsistency prevents geometric perception from being directly aligned with robotic actions defined on the real-world scale. To address this limitation, we propose Metric-Aware Geometry Perception (MAGP), an end-to-end, plug-and-play framework for me
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-27T02:07:22.000Z
First collected: 2026-09-21T09:11:58.312Z. This is not the publication date.