Protocol for training/testing Partially visible data

[yewzijian]

Hi, first of all thanks for the good work and for releasing the source code. I would like to better understand the protocol for training/testing on partially visible data.

1. In the paper, you mentioned that you resample the source point cloud. But I understand that the source point cloud is the simulated 2.5D partial scan. Does that mean you simulate the capturing of the source point cloud from a different angle?
2. If the source and template are resampled in each iteration, does that mean the jacobian has to be recomputed for each iteration during both training and inference?
3. During training, since the number of visible points can vary, how do you handle this?
4. Do you also pretrain the classifier on partial data?

Thank you.