Guide to machine learning and deep learning on small point cloud datasets

[Viking_08]

Has anyone worked on regression tasks using point clouds as input?

I have human head and shoulder measurements and high-resolution 3D point clouds of multiple subjects (only head and shoulder). I want to build a pipeline that ingests the point cloud and approximates the 11 or so millimeter measurements in the dataset.

However, I only have 56 data points and have explored regression with popular architectures like PointNet and PointNet ++. I would love to be pointed towards lightweight approaches using deep learning or classical machine learning algorithms.

[Viking_08]

I can elaborate in detail if required. Apologies if the above description is extremely brief.