SOURCE-LINKED INTELLIGENCE
GALoc: Gravity Aligned Wireframes for Depth-Free Monocular Floorplan Localization
Floorplans are compact, appearance-invariant maps ideal for indoor localization, yet existing methods rely on depth networks that are brittle in cluttered scenes. We propose GALoc, a geometry-first framework that replaces depth prediction with gravity-aligned wireframes that satisfy verticality and coplanarity by construction. Given monocular RGB, camera intrinsics, relative poses, and IMU orientation, GALoc constructs a linear constraint matrix encoding verticality and coplanarity, and finds the camera gauge minimizing its smallest singular value via global search. The rectified wireframes ar
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T07:56:14.000Z
First collected: 2026-09-20T20:22:01.598Z. This is not the publication date.