Neural Stochastic Screened Poisson Reconstruction
Silvia Sellán Alec Jacobson
Reconstructing a surface from a point cloud is an underdetermined problem. We
use a neural network to study and quantify this reconstruction uncertainty
under a Poisson smoothness prior. Our algorithm addresses the main limitations
of existing work and can be fully integrated into the 3D scanning pipeline,
from obtaining an initial reconstruction to deciding on the next best sensor
position and updating the reconstruction upon capturing more data.