Gallery Image


teaser : We present Points2Surf, a method to reconstruct an accurate implicit surface from a noisy point cloud. Unlike current data-driven surface reconstruction methods like DeepSDF and AtlasNet, it is patch-based, improves detail reconstruction, and unlike Screened Poisson Reconstruction (SPR), a learned prior of low-level patch shapes improves reconstruction accuracy. Note the quality of reconstructions, both geometric and topological, against the original surfaces. The ability of Points2Surf to generalize to new shapes makes it the first learning-based approach with significant generalization ability under both geometric and topological variations.


This image has been taken from the following publication:
Philipp Erler, Paul Guerrero, Stefan Ohrhallinger, Michael Wimmer, Niloy Mitra
Points2Surf: Learning Implicit Surfaces from Point Clouds
In Computer Vision -- ECCV 2020, pages 108-124. October 2020.
[points2surf_paper] [short video]
Conference Paper