Lecture Notes

The full set of slides is available for download here:

Part 1: download (129 MB)

Part 2: download (8 MB)

Here are some useful references to the intrinsic constructions considered in the tutorial:

Learning shape correspondence with anisotropic convolutional neural networks

D. Boscaini, J. Masci, E. Rodola, M. Bronstein

arXiv 1605.06437 - Accepted to NIPS 2016

Matching deformable objects in clutter

L. Cosmo, E. Rodola, J. Masci, A. Torsello, M. Bronstein

Proc. 3DV 2016

Anisotropic diffusion descriptors

D. Boscaini, J. Masci, E. Rodola, M. Bronstein, D. Cremers

CGF 35(2), 2016 - Proc. Eurographics 2016

Geodesic convolutional neural networks on Riemannian manifolds

J. Masci, D. Boscaini, M. Bronstein, P. Vandergheynst

Proc. 3dRR 2015

Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks

D. Boscaini, J. Masci, S. Melzi, M. Bronstein, U. Castellani, P. Vandergheynst

CGF 34(5), 2015 - Proc. SGP 2015

Dense non-rigid shape correspondence using random forests

E. Rodola, S. Rota Bulo, T. Windheuser, M. Vestner, D. Cremers

Proc. CVPR 2014

Learning spectral descriptors for deformable shape correspondence

R. Litman, A. Bronstein

TPAMI 36(1), 2013