A hierarchical offline-online framework for 3D global relocalization using synthetic LiDAR and descriptor retrieval achieves 3-second average time and 8 cm accuracy with order-of-magnitude efficiency gains over prior methods.
Bevplace++: Fast, robust, and lightweight lidar global localization for unmanned ground vehicles
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FP16 quantization preserves accuracy in BEV-based LiDAR place recognition at lower cost while INT8 degradation depends on the network architecture.
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Offline-Online Hierarchical 3D Global Relocalization With Synthetic LiDAR Sensing and Descriptor-Space Retrieval
A hierarchical offline-online framework for 3D global relocalization using synthetic LiDAR and descriptor retrieval achieves 3-second average time and 8 cm accuracy with order-of-magnitude efficiency gains over prior methods.
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EdgeLPR: On the Deep Neural Network trade-off between Precision and Performance in LiDAR Place Recognition
FP16 quantization preserves accuracy in BEV-based LiDAR place recognition at lower cost while INT8 degradation depends on the network architecture.