4 papers
FUSE: A Flow-based Mapping Between Shapes
Lorenzo Olearo, Giulio Viganò, Daniele Baieri +2
We introduce a novel neural representation for maps between 3D shapes based on flow-matching models, which is computationally efficient and supports cross-representation shape matc…
Volumetric Functional Maps
Filippo Maggioli, Simone Melzi, Marco Livesu
Computing volumetric correspondences between 3D shapes is a prominent tool for medical and industrial applications. In this work, we pave the way for spectral volume mapping, exten…
SShaDe: scalable shape deformation via local representations
Filippo Maggioli, Daniele Baieri, Zorah Lähner +1
With the increase in computational power for the available hardware, the demand for high-resolution data in computer graphics applications increases. Consequently, classical geomet…
Implicit-ARAP: Efficient Handle-Guided Neural Field Deformation via Local Patch Meshing
Daniele Baieri, Filippo Maggioli, Emanuele Rodolà +2
Neural fields have emerged as a powerful representation for 3D geometry, enabling compact and continuous modeling of complex shapes. Despite their expressive power, manipulating ne…