Obserwuj
Davide Boscaini
Davide Boscaini
Researcher, Fondazione Bruno Kessler
Zweryfikowany adres z fbk.eu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
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
23742017
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
9422015
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
7092020
Learning shape correspondence with anisotropic convolutional neural networks
D Boscaini, J Masci, E Rodolà, M Bronstein
Advances in neural information processing systems 29, 2016
6292016
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
2552015
Anisotropic diffusion descriptors
D Boscaini, J Masci, E Rodolà, MM Bronstein, D Cremers
Computer Graphics Forum 35 (2), 431-441, 2016
1492016
Learning general and distinctive 3D local deep descriptors for point cloud registration
F Poiesi, D Boscaini
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 3979-3985, 2022
82*2022
Shapenet: Convolutional neural networks on non-euclidean manifolds
J Masci, D Boscaini, M Bronstein, P Vandergheynst
692015
Geometric deep learning
J Masci, E Rodolà, D Boscaini, MM Bronstein, H Li
SIGGRAPH ASIA 2016 Courses, 1-50, 2016
592016
Distinctive 3D local deep descriptors
F Poiesi, D Boscaini
2020 25th International conference on pattern recognition (ICPR), 5720-5727, 2021
552021
Shape‐from‐operator: Recovering shapes from intrinsic operators
D Boscaini, D Eynard, D Kourounis, MM Bronstein
Computer Graphics Forum 34 (2), 265-274, 2015
502015
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
392021
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
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
222020
Clustered Dynamic Graph CNN for Biometric 3D Hand Shape Recognition
J Svoboda, P Astolfi, D Boscaini, J Masci, MM Bronstein
Proceedings of the IEEE International Joint Conference on Biometrics, 2020
152020
Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection
ML Mekhalfi, D Boscaini, F Poiesi
arXiv preprint arXiv:2308.15353, 2023
102023
Revisiting Fully Convolutional Geometric Features for Object 6D Pose Estimation
J Corsetti, D Boscaini, F Poiesi
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
92023
Freeze: Training-free zero-shot 6d pose estimation with geometric and vision foundation models
A Caraffa, D Boscaini, A Hamza, F Poiesi
European Conference on Computer Vision, 414-431, 2024
7*2024
The MONET dataset: Multimodal drone thermal dataset recorded in rural scenarios
L Riz, A Caraffa, M Bortolon, ML Mekhalfi, D Boscaini, A Moura, J Antunes, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
72023
System and a method for learning features on geometric domains
M Bronstein, D Boscaini, J Masci, P Vandergheynst
US Patent 10,013,653, 2018
72018
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
6*2014
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–20