Davide Boscaini

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 39

Top Topics

Computed Tomography Scans

Deformable Shapes

Convolutional Neural Networks

Top Venues

Comput. Graph. Forum

Publications

Luigi Riz, Sergio Povoli, Andrea Caraffa, Davide Boscaini, Mohamed Lamine Mekhalfi, Paul Chippendale, Marjut Turtiainen, Birgitta Partanen, Laura Smith Ballester, J. Francisco Blanes Noguera, Alessio Franchi, Elisa Castelli, Giacomo Piccinini, Luca Marchesotti, Micael Santos Couceiro, Fabio Poiesi
Wild Berry image dataset collected in Finnish forests and peatlands using drones. CoRR (2024)
Jaime Corsetti, Davide Boscaini, Francesco Giuliari, Changjae Oh, Andrea Cavallaro, Fabio Poiesi
High-resolution open-vocabulary object 6D pose estimation. CoRR (2024)
Mohamed Lamine Mekhalfi, Davide Boscaini, Fabio Poiesi
Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection. BMVC (2023)
Pietro Astolfi, Ruben Verhagen, Laurent Petit, Emanuele Olivetti, Silvio Sarubbo, Jonathan Masci, Davide Boscaini, Paolo Avesani
Supervised tractogram filtering using Geometric Deep Learning. Medical Image Anal. 90 (2023)
Jaime Corsetti, Davide Boscaini, Changjae Oh, Andrea Cavallaro, Fabio Poiesi
Open-vocabulary object 6D pose estimation. CoRR (2023)
Fabio Poiesi, Davide Boscaini
Learning General and Distinctive 3D Local Deep Descriptors for Point Cloud Registration. IEEE Trans. Pattern Anal. Mach. Intell. 45 (3) (2023)
Andrea Caraffa, Davide Boscaini, Amir Hamza, Fabio Poiesi
Object 6D pose estimation meets zero-shot learning. CoRR (2023)
Mohamed Lamine Mekhalfi, Davide Boscaini, Fabio Poiesi
Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection. CoRR (2023)
Davide Boscaini, Fabio Poiesi
PatchMixer: Rethinking network design to boost generalization for 3D point cloud understanding. CoRR (2023)
Luigi Riz, Andrea Caraffa, Matteo Bortolon, Mohamed Lamine Mekhalfi, Davide Boscaini, André Moura, José Antunes, André Dias, Hugo Silva, Andreas Leonidou, Christos Constantinides, Christos Keleshis, Dante Abate, Fabio Poiesi
The MONET dataset: Multimodal drone thermal dataset recorded in rural scenarios. CoRR (2023)
Jaime Corsetti, Davide Boscaini, Fabio Poiesi
Revisiting Fully Convolutional Geometric Features for Object 6D Pose Estimation. ICCV (Workshops) (2023)
Luigi Riz, Andrea Caraffa, Matteo Bortolon, Mohamed Lamine Mekhalfi, Davide Boscaini, André Moura, José Antunes, André Dias, Hugo Silva, Andreas Leonidou, Christos Constantinides, Christos Keleshis, Dante Abate, Fabio Poiesi
The MONET dataset: Multimodal drone thermal dataset recorded in rural scenarios. CVPR Workshops (2023)
Jaime Corsetti, Davide Boscaini, Fabio Poiesi
Revisiting Fully Convolutional Geometric Features for Object 6D Pose Estimation. CoRR (2023)
Davide Boscaini, Fabio Poiesi
PatchMixer: Rethinking network design to boost generalization for 3D point cloud understanding. Image Vis. Comput. 137 (2023)
Pietro Astolfi, Ruben Verhagen, Laurent Petit, Emanuele Olivetti, Silvio Sarubbo, Jonathan Masci, Davide Boscaini, Paolo Avesani
Supervised Tractogram Filtering using Geometric Deep Learning. CoRR (2022)
Fabio Poiesi, Davide Boscaini
Generalisable and distinctive 3D local deep descriptors for point cloud registration. CoRR (2021)
Davide Boscaini, Fabio Poiesi, Stefano Messelodi, Ayman Younes, Donato A. Grande
Localisation of Defects in Volumetric Computed Tomography Scans of Valuable Wood Logs. ICPR Workshops (4) (2020)
Fabio Poiesi, Davide Boscaini
Distinctive 3D local deep descriptors. ICPR (2020)
Antonio Alliegro, Davide Boscaini, Tatiana Tommasi
Joint Supervised and Self-Supervised Learning for 3D Real World Challenges. ICPR (2020)
Antonio Alliegro, Davide Boscaini, Tatiana Tommasi
Joint Supervised and Self-Supervised Learning for 3D Real-World Challenges. CoRR (2020)
Mohamed Ilyes Lakhal, Davide Boscaini, Fabio Poiesi, Oswald Lanz, Andrea Cavallaro
Novel-View Human Action Synthesis. ACCV (4) (2020)
Jan Svoboda, Pietro Astolfi, Davide Boscaini, Jonathan Masci, Michael M. Bronstein
Clustered Dynamic Graph CNN for Biometric 3D Hand Shape Recognition. IJCB (2020)
Levi O. Vasconcelos, Massimiliano Mancini, Davide Boscaini, Samuel Rota Bulò, Barbara Caputo, Elisa Ricci
Shape Consistent 2D Keypoint Estimation under Domain Shift. ICPR (2020)
Davide Boscaini, Fabio Poiesi
3D Shape Segmentation with Geometric Deep Learning. CoRR (2020)
Fabio Poiesi, Davide Boscaini
Distinctive 3D local deep descriptors. CoRR (2020)
Pietro Astolfi, Ruben Verhagen, Laurent Petit, Emanuele Olivetti, Jonathan Masci, Davide Boscaini, Paolo Avesani
Tractogram Filtering of Anatomically Non-plausible Fibers with Geometric Deep Learning. MICCAI (7) (2020)
Mohamed Ilyes Lakhal, Davide Boscaini, Fabio Poiesi, Oswald Lanz, Andrea Cavallaro
Novel-View Human Action Synthesis. CoRR (2020)
Pietro Astolfi, Ruben Verhagen, Laurent Petit, Emanuele Olivetti, Jonathan Masci, Davide Boscaini, Paolo Avesani
Tractogram filtering of anatomically non-plausible fibers with geometric deep learning. CoRR (2020)
Antonio Alliegro, Davide Boscaini, Tatiana Tommasi
Self-Supervision for 3D Real-World Challenges. ECCV Workshops (1) (2020)
Levi O. Vasconcelos, Massimiliano Mancini, Davide Boscaini, Samuel Rota Bulò, Barbara Caputo, Elisa Ricci
Shape Consistent 2D Keypoint Estimation under Domain Shift. CoRR (2020)
Levi O. Vasconcelos, Massimiliano Mancini, Davide Boscaini, Barbara Caputo, Elisa Ricci
Structured Domain Adaptation for 3D Keypoint Estimation. 3DV (2019)
Davide Boscaini, Fabio Poiesi
3D Shape Segmentation with Geometric Deep Learning. ICIAP (1) (2019)
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein
Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs. CVPR (2017)
Michael M. Bronstein, Evangelos Kalogerakis, Emanuele Rodolà, Jonathan Masci, Davide Boscaini
Deep Learning for Shape Analysis. Eurographics (Tutorials) (2016)
Jonathan Masci, Emanuele Rodolà, Davide Boscaini, Michael M. Bronstein, Hao Li
Geometric deep learning. SIGGRAPH ASIA Courses (2016)
Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein
Learning shape correspondence with anisotropic convolutional neural networks. CoRR (2016)
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein
Geometric deep learning on graphs and manifolds using mixture model CNNs. CoRR (2016)
Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein
Learning shape correspondence with anisotropic convolutional neural networks. NIPS (2016)
Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers
Anisotropic Diffusion Descriptors. Comput. Graph. Forum 35 (2) (2016)
Davide Boscaini, Jonathan Masci, Simone Melzi, Michael M. Bronstein, Umberto Castellani, Pierre Vandergheynst
Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks. Comput. Graph. Forum 34 (5) (2015)
Davide Boscaini, Davide Eynard, Drosos Kourounis, Michael M. Bronstein
Shape-from-Operator: Recovering Shapes from Intrinsic Operators. Comput. Graph. Forum 34 (2) (2015)
Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst
Geodesic Convolutional Neural Networks on Riemannian Manifolds. ICCV Workshops (2015)
Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst
ShapeNet: Convolutional Neural Networks on Non-Euclidean Manifolds. CoRR (2015)
Davide Boscaini, Davide Eynard, Michael M. Bronstein
Shape-from-intrinsic operator. CoRR (2014)
Davide Boscaini, Umberto Castellani
A sparse coding approach for local-to-global 3D shape description. Vis. Comput. 30 (11) (2014)
Davide Boscaini, Ramunas Girdziusas, Michael M. Bronstein
Coulomb Shapes: Using Electrostatic Forces for Deformation-invariant Shape Representation. 3DOR@Eurographics (2014)
Davide Boscaini, Umberto Castellani
Local Signature Quantization by Sparse Coding. 3DOR@Eurographics (2013)