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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.

Publication

This image has been taken from the following publication:
2020
Philipp Erler, Paul Guerrero, Stefan Ohrhallinger, Michael Wimmer, Niloy Mitra
Points2Surf: Learning Implicit Surfaces from Point Clouds
todo, todo:todo-todo, August 2020. [Github Repo] [Arxiv Pre-Print]
Journal Paper with Conference Talk