In this post I describe how I re-implemented the main idea of the paper ‘Learning Sparse Singularities for Cross Field Design’: a C++ app (geometry-central, Eigen, Spectra) computes features and labels, a DiffusionNet in PyTorch predicts singularities, and trivial connections rebuild the cross field.