Concept
Théorème de l'invariance du domaine
Publications associées (8)
Generalised Implicit Neural Representations
We consider the problem of learning implicit neural representations (INRs) for signals on non-Euclidean domains. In the Euclidean case, INRs are trained on a discrete sampling of a signal over a regular lattice. Here, we assume that the continuous signal e ...
2022Smooth Shapes with Spherical Topology: Beyond Traditional Modeling, Efficient Deformation, and Interaction
Michaël Unser, Pablo Garcia-Amorena Garcia, Daniel Andreas Schmitter
Existing shape models with spherical topology are typically designed either in the discrete domain using interpolating polygon meshes or in the continuous domain using smooth but non-interpolating schemes such as subdivision or NURBS. Both polygon models a ...
2017Smoothly Deformable Spheres: Modeling, Deformation, and Interaction
Michaël Unser, Pablo Garcia-Amorena Garcia, Daniel Andreas Schmitter
Existing shape models with spherical topology are typically designed either in the discrete domain using interpolating polygon meshes or in the continuous domain using smooth but non-interpolating schemes such as NURBS. Polygon models and subdivision metho ...
ACM2016