3.7k citations · 7.1k across the 79 of their papers we have counts for
4 papers · 2 filters
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…
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-…
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…
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence
Or Litany, Tal Remez, Emanuele Rodolà +2
We introduce a new framework for learning dense correspondence between deformable 3D shapes. Existing learning based approaches model shape correspondence as a labelling problem, w…