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Davide Boscaini
Title
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Cited by
Year
Geometric deep learning on graphs and manifolds using mixture model cnns
F Monti, D Boscaini, J Masci, E Rodola, J Svoboda, MM Bronstein
Proceedings of the IEEE conference on computer vision and pattern …, 2017
14652017
Geodesic Convolutional Neural Networks on Riemannian Manifolds
J Masci, D Boscaini, MM Bronstein, P Vandergheynst
International IEEE Workshop on 3D Representation and Recognition (3dRR), 2015
6722015
Learning shape correspondence with anisotropic convolutional neural networks
D Boscaini, J Masci, E Rodolà, M Bronstein
Advances in neural information processing systems 29, 2016
4812016
Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning
P Gainza, F Sverrisson, F Monti, E Rodola, D Boscaini, MM Bronstein, ...
Nature Methods 17 (2), 184-192, 2020
2422020
Learning class‐specific descriptors for deformable shapes using localized spectral convolutional networks
D Boscaini, J Masci, S Melzi, MM Bronstein, U Castellani, ...
Computer graphics forum 34 (5), 13-23, 2015
2112015
Anisotropic diffusion descriptors
D Boscaini, J Masci, E Rodolà, MM Bronstein, D Cremers
Computer Graphics Forum 35 (2), 431-441, 2016
1352016
Shapenet: Convolutional neural networks on non-euclidean manifolds
J Masci, D Boscaini, M Bronstein, P Vandergheynst
562015
Shape‐from‐operator: Recovering shapes from intrinsic operators
D Boscaini, D Eynard, D Kourounis, MM Bronstein
Computer Graphics Forum 34 (2), 265-274, 2015
452015
Geometric deep learning
J Masci, E Rodolà, D Boscaini, MM Bronstein, H Li
SIGGRAPH ASIA 2016 Courses, 1-50, 2016
382016
Distinctive 3D local deep descriptors
F Poiesi, D Boscaini
2020 25th International conference on pattern recognition (ICPR), 5720-5727, 2021
192021
Joint supervised and self-supervised learning for 3d real world challenges
A Alliegro, D Boscaini, T Tommasi
2020 25th International Conference on Pattern Recognition (ICPR), 6718-6725, 2021
172021
Generalisable and distinctive 3D local deep descriptors for point cloud registration
F Poiesi, D Boscaini
arXiv preprint arXiv:2105.10382, 2021
92021
Tractogram filtering of anatomically non-plausible fibers with geometric deep learning
P Astolfi, R Verhagen, L Petit, E Olivetti, J Masci, D Boscaini, P Avesani
International Conference on Medical Image Computing and Computer-Assisted …, 2020
82020
A sparse coding approach for local-to-global 3D shape description
D Boscaini, U Castellani
The Visual Computer, 2014
72014
System and a method for learning features on geometric domains
M Bronstein, D Boscaini, J Masci, P Vandergheynst
US Patent 10,013,653, 2018
52018
Coulomb shapes: using electrostatic forces for deformation-invariant shape representation
D Boscaini, R Girdziusaz, MM Bronstein
Eurographics Workshop on 3D Object Retrieval (3DOR), 9-15, 2014
5*2014
Novel-view human action synthesis
MI Lakhal, D Boscaini, F Poiesi, O Lanz, A Cavallaro
Proceedings of the Asian Conference on Computer Vision, 2020
22020
Shape-from-intrinsic operator
D Boscaini, D Eynard, MM Bronstein
arXiv preprint arXiv:1406.1925, 2014
22014
Local signature quantization by sparse coding
D Boscaini, U Castellani
Eurographics Workshop on 3D Object Retrieval (3DOR), 9-16, 2013
22013
Learning general and distinctive 3D local deep descriptors for point cloud registration
F Poiesi, D Boscaini
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
12022
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Articles 1–20