372 citations · 641 across the 71 of their papers we have counts for
6 papers · 1 filter
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…
Effective Rotation-invariant Point CNN with Spherical Harmonics kernels
Adrien Poulenard, Marie-Julie Rakotosaona, Yann Ponty +1
We present a novel rotation invariant architecture operating directly on point cloud data. We demonstrate how rotation invariance can be injected into a recently proposed point-bas…
Spectral Coarsening of Geometric Operators
Hsueh-Ti Derek Liu, Alec Jacobson, Maks Ovsjanikov
We introduce a novel approach to measure the behavior of a geometric operator before and after coarsening. By comparing eigenvectors of the input operator and its coarsened counter…
OperatorNet: Recovering 3D Shapes From Difference Operators
Ruqi Huang, Marie-Julie Rakotosaona, Panos Achlioptas +2
This paper proposes a learning-based framework for reconstructing 3D shapes from functional operators, compactly encoded as small-sized matrices. To this end we introduce a novel n…
ZoomOut: Spectral Upsampling for Efficient Shape Correspondence
Simone Melzi, Jing Ren, Emanuele Rodolà +3
We present a simple and efficient method for refining maps or correspondences by iterative upsampling in the spectral domain that can be implemented in a few lines of code. Our mai…
PointCleanNet: Learning to Denoise and Remove Outliers from Dense Point Clouds
Marie-Julie Rakotosaona, Vittorio La Barbera, Paul Guerrero +2
Point clouds obtained with 3D scanners or by image-based reconstruction techniques are often corrupted with significant amount of noise and outliers. Traditional methods for point…