  We present a pipeline for parametric wireframe extraction from densely
sampled point clouds. Our approach processes a scalar distance field that
represents proximity to the nearest sharp feature curve. In intermediate
stages, it detects corners, constructs curve segmentation, and builds a
topological graph fitted to the wireframe. As an output, we produce parametric
spline curves that can be edited and sampled arbitrarily. We evaluate our
method on 50 complex 3D shapes and compare it to the novel deep learning-based
technique, demonstrating superior quality.
