PolyCube-Maps
By Marco Tarini, Kai Hormann, Paolo Cignoni, Claudio Montani. 2004
280 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- Bruno Lévy
- Alla Sheffer
- Pierre Alliez
- Nicolas Ray
- Wan-Chiu Li
- Andreas Geiger
- Pascal Fua
- Julian Straub
In Computer Graphics and Computer-Aided Design
- Bruno Lévy
- Alla Sheffer
- Pierre Alliez
- Nicolas Ray
- Wan-Chiu Li
- Andreas Geiger
- Pascal Fua
- Julian Straub
Citations in the corpus
- DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation (2019, methodology): “Other recent works [3] use poly-cube mapping [51] for shape optimization.”
- Geodesic Convolutional Shape Optimization (2018, methodology): “To overcome this difficulty, we propose to exploit the properties of cube and poly-cube maps (Tarini et al., 2004), which allow the remeshing of 3D shapes homotopic to spheres such as those of cars or bicycles shells as semi-regular quad-meshes with few irregular vertices, a uniform tessellation…”
- Periodic global parameterization (2006, methodology): “A similar approach is used in polycube maps [Tarini et al. 2004].”