Table 3.

Hyperparameter configuration for model training.

Parameter	Meaning	Setting
Input features	Point attributes before feature augmentation	$(x,y,z,\mathrm{RCS},\mathrm{Intensity},\mathrm{Velocity})$
Raw input channels	Number of raw point attributes	6
Output classes	Background and face guard	2
Input points	Points per training sample	2560
Batch size	Samples per update	32
Epochs	Training epochs	100
Optimizer	Parameter update method	Adam
Learning rate	Initial step size	0.001
Loss function	Point-level classification loss	Focal loss