372 citations · 641 across the 71 of their papers we have counts for
4 papers · 1 filter
Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution
Adrien Poulenard, Maks Ovsjanikov, Leonidas J. Guibas
A wide range of techniques have been proposed in recent years for designing neural networks for 3D data that are equivariant under rotation and translation of the input. Most appro…
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment
Arianna Rampini, Irene Tallini, Maks Ovsjanikov +2
We consider the problem of localizing relevant subsets of non-rigid geometric shapes given only a partial 3D query as the input. Such problems arise in several challenging tasks in…
Isospectralization, or how to hear shape, style, and correspondence
Luca Cosmo, Mikhail Panine, Arianna Rampini +3
The question whether one can recover the shape of a geometric object from its Laplacian spectrum ('hear the shape of the drum') is a classical problem in spectral geometry with a b…
PCPNET: Learning Local Shape Properties from Raw Point Clouds
Paul Guerrero, Yanir Kleiman, Maks Ovsjanikov +1
In this paper, we propose PCPNet, a deep-learning based approach for estimating local 3D shape properties in point clouds. In contrast to the majority of prior techniques that conc…