A geometry-consistent framework that turns LiDAR scans into camera-style depth images with intensity and surface normals, and trains with a distance-aware contrastive loss, achieves state-of-the-art cross-modal place recognition on KITTI and KITTI-360.
From coarse to fine: Robust hierarchical localization at large scale
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
GeoUniPR: A Geometry-Consistent Unified Framework for Cross-Modal Place Recognition
A geometry-consistent framework that turns LiDAR scans into camera-style depth images with intensity and surface normals, and trains with a distance-aware contrastive loss, achieves state-of-the-art cross-modal place recognition on KITTI and KITTI-360.