3.7k citations · 7.1k across the 79 of their papers we have counts for
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Deformable Shape Completion with Graph Convolutional Autoencoders
Or Litany, Alex Bronstein, Michael Bronstein +1
The availability of affordable and portable depth sensors has made scanning objects and people simpler than ever. However, dealing with occlusions and missing parts is still a sign…
Subspace Least Squares Multidimensional Scaling
Amit Boyarski, Alex M. Bronstein, Michael M. Bronstein
Multidimensional Scaling (MDS) is one of the most popular methods for dimensionality reduction and visualization of high dimensional data. Apart from these tasks, it also found app…
Efficient Deformable Shape Correspondence via Kernel Matching
Zorah Lähner, Matthias Vestner, Amit Boyarski +8
We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-…
Localized Manifold Harmonics for Spectral Shape Analysis
Simone Melzi, Emanuele Rodolà, Umberto Castellani +1
The use of Laplacian eigenfunctions is ubiquitous in a wide range of computer graphics and geometry processing applications. In particular, Laplacian eigenbases allow generalizing…
Generative Convolutional Networks for Latent Fingerprint Reconstruction
Jan Svoboda, Federico Monti, Michael M. Bronstein
Performance of fingerprint recognition depends heavily on the extraction of minutiae points. Enhancement of the fingerprint ridge pattern is thus an essential pre-processing step t…
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters
Ron Levie, Federico Monti, Xavier Bresson +1
The rise of graph-structured data such as social networks, regulatory networks, citation graphs, and functional brain networks, in combination with resounding success of deep learn…