PlanaReLoc: Camera Relocalization in 3D Planar Primitives via Region-Based Structure Matching
Hanqiao Ye, Yuzhou Liu, Yangdong Liu, Shuhan Shen

TL;DR
PlanaReLoc introduces a novel camera relocalization method using 3D planar primitives and region-based structure matching, enabling reliable relocalization in structured environments without textured maps or pose priors.
Contribution
The paper pioneers the use of planar primitives and a deep matching framework for lightweight 6-DoF camera relocalization in structured environments.
Findings
Outperforms point-based methods in relocalization accuracy
Effective without textured or colored maps
No need for pose priors or per-scene training
Abstract
While structure-based relocalizers have long strived for point correspondences when establishing or regressing query-map associations, in this paper, we pioneer the use of planar primitives and 3D planar maps for lightweight 6-DoF camera relocalization in structured environments. Planar primitives, beyond being fundamental entities in projective geometry, also serve as region-based representations that encapsulate both structural and semantic richness. This motivates us to introduce PlanaReLoc, a streamlined plane-centric paradigm where a deep matcher associates planar primitives across the query image and the map within a learned unified embedding space, after which the 6-DoF pose is solved and refined under a robust framework. Through comprehensive experiments on the ScanNet and 12Scenes datasets across hundreds of scenes, our method demonstrates the superiority of planar primitives…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRobotics and Sensor-Based Localization · 3D Shape Modeling and Analysis · Advanced Image and Video Retrieval Techniques
