GeoUniPR: A Geometry-Consistent Unified Framework for Cross-Modal Place Recognition
Cross-modal place recognition (CMPR) aims to identify the same location across heterogeneous sensing modalities, such as vision and LiDAR. Existing methods commonly bridge the modality gap using complex alignment modules, multi-stage training, or full fine-tuning of pretrained backbones. In this work, we revisit CMPR from the perspective of geometric consistency and propose GeoUniPR, a unified and concise geometry-consistent framework. GeoUniPR reduces cross-modal discrepancy at the representation level by projecting LiDAR point clouds into the camera perspective to construct Geometry-Consistent depth image views (DIV), which establish direct RGB-LiDAR correspondence. We further augment D...
| Authors | Wonbong Kim, Jiatong Xiao, Rui Li et al. |
|---|---|
| Primary category | cs.CV |
| Published | 10 August 2026 |
| Last updated at source | 10 August 2026 |
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