FP16 quantization preserves accuracy in BEV-based LiDAR place recognition at lower cost while INT8 degradation depends on the network architecture.
Intensity scan context: Coding intensity and geometry relations for loop closure detection
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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.