LTR² is the first LiDAR-teach radar-repeat navigation system using a Cross-Modal Registration network and adaptive fine-tuning to achieve centimeter-level accuracy and robustness over 40+ km deployments in adverse conditions.
Cmrnext: Camera to lidar matching in the wild for localization and extrinsic calibration
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
DualViewMapDet fuses prior-traversal point cloud maps into camera features via dual perspective-view and bird's-eye-view encoding to improve 3D detection and tracking without LiDAR.
citing papers explorer
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LiDAR Teach, Radar Repeat: Robust Cross-Modal Navigation in Degenerate and Varying Environments
LTR² is the first LiDAR-teach radar-repeat navigation system using a Cross-Modal Registration network and adaptive fine-tuning to achieve centimeter-level accuracy and robustness over 40+ km deployments in adverse conditions.
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Leveraging Previous-Traversal Point Cloud Map Priors for Camera-Based 3D Object Detection and Tracking
DualViewMapDet fuses prior-traversal point cloud maps into camera features via dual perspective-view and bird's-eye-view encoding to improve 3D detection and tracking without LiDAR.