3 papers
cs.CV2024
PoNQ: a Neural QEM-based Mesh Representation
Nissim Maruani, Maks Ovsjanikov, Pierre Alliez +1
Although polygon meshes have been a standard representation in geometry processing, their irregular and combinatorial nature hinders their suitability for learning-based applicatio…
cs.CV2023
VoroMesh: Learning Watertight Surface Meshes with Voronoi Diagrams
Nissim Maruani, Roman Klokov, Maks Ovsjanikov +2
In stark contrast to the case of images, finding a concise, learnable discrete representation of 3D surfaces remains a challenge. In particular, while polygon meshes are arguably t…
cs.GR2016
Error-Bounded and Feature Preserving Surface Remeshing with Minimal Angle Improvement
Kaimo Hu, Dong-Ming Yan, David Bommes +2
The typical goal of surface remeshing consists in finding a mesh that is (1) geometrically faithful to the original geometry, (2) as coarse as possible to obtain a low-complexity r…