Davide Boscaini

According to our database, Davide Boscaini authored at least 36 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Exploring Fine-grained Retail Product Discrimination with Zero-shot Object Classification Using Vision-Language Models.

Anil Osman Tur, Alessandro Conti, Cigdem Beyan, Davide Boscaini, Roberto Larcher, Stefano Messelodi, Fabio Poiesi, Elisa Ricci

CoRR, 2024

High-resolution open-vocabulary object 6D pose estimation.

Jaime Corsetti, Davide Boscaini, Francesco Giuliari, Changjae Oh, Andrea Cavallaro, Fabio Poiesi

CoRR, 2024

Wild Berry image dataset collected in Finnish forests and peatlands using drones.

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

CoRR, 2024

FreeZe: Training-Free Zero-Shot 6D Pose Estimation with Geometric and Vision Foundation Models.

Andrea Caraffa, Davide Boscaini, Amir Hamza, Fabio Poiesi

Proceedings of the Computer Vision - ECCV 2024, 2024

Open-vocabulary object 6D pose estimation.

Jaime Corsetti, Davide Boscaini, Changjae Oh, Andrea Cavallaro, Fabio Poiesi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Supervised tractogram filtering using Geometric Deep Learning.

Pietro Astolfi, Ruben Verhagen, Laurent Petit, Emanuele Olivetti, Silvio Sarubbo, Jonathan Masci, Davide Boscaini, Paolo Avesani

Medical Image Anal., December, 2023

PatchMixer: Rethinking network design to boost generalization for 3D point cloud understanding.

Davide Boscaini, Fabio Poiesi

Image Vis. Comput., September, 2023

Learning General and Distinctive 3D Local Deep Descriptors for Point Cloud Registration.

Fabio Poiesi, Davide Boscaini

IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

Object 6D pose estimation meets zero-shot learning.

Andrea Caraffa, Davide Boscaini, Amir Hamza, Fabio Poiesi

CoRR, 2023

Revisiting Fully Convolutional Geometric Features for Object 6D Pose Estimation.

Jaime Corsetti, Davide Boscaini, Fabio Poiesi

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

The MONET dataset: Multimodal drone thermal dataset recorded in rural scenarios.

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Detect, Augment, Compose, and Adapt: Four Steps for Unsupervised Domain Adaptation in Object Detection.

Mohamed Lamine Mekhalfi, Davide Boscaini, Fabio Poiesi

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2021

Generalisable and distinctive 3D local deep descriptors for point cloud registration.

Fabio Poiesi, Davide Boscaini

CoRR, 2021

2020

Tractogram Filtering of Anatomically Non-plausible Fibers with Geometric Deep Learning.

Pietro Astolfi, Ruben Verhagen, Laurent Petit, Emanuele Olivetti, Jonathan Masci, Davide Boscaini, Paolo Avesani

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Shape Consistent 2D Keypoint Estimation under Domain Shift.

Levi O. Vasconcelos, Massimiliano Mancini, Davide Boscaini, Samuel Rota Bulò, Barbara Caputo, Elisa Ricci

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Distinctive 3D local deep descriptors.

Fabio Poiesi, Davide Boscaini

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Localisation of Defects in Volumetric Computed Tomography Scans of Valuable Wood Logs.

Davide Boscaini, Fabio Poiesi, Stefano Messelodi, Ayman Younes, Donato A. Grande

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Joint Supervised and Self-Supervised Learning for 3D Real World Challenges.

Antonio Alliegro, Davide Boscaini, Tatiana Tommasi

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Clustered Dynamic Graph CNN for Biometric 3D Hand Shape Recognition.

Jan Svoboda, Pietro Astolfi, Davide Boscaini, Jonathan Masci, Michael M. Bronstein

Proceedings of the 2020 IEEE International Joint Conference on Biometrics, 2020

Self-Supervision for 3D Real-World Challenges.

Antonio Alliegro, Davide Boscaini, Tatiana Tommasi

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

Novel-View Human Action Synthesis.

Mohamed Ilyes Lakhal, Davide Boscaini, Fabio Poiesi, Oswald Lanz, Andrea Cavallaro

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019

3D Shape Segmentation with Geometric Deep Learning.

Davide Boscaini, Fabio Poiesi

Proceedings of the Image Analysis and Processing - ICIAP 2019, 2019

Structured Domain Adaptation for 3D Keypoint Estimation.

Levi O. Vasconcelos, Massimiliano Mancini, Davide Boscaini, Barbara Caputo, Elisa Ricci

Proceedings of the 2019 International Conference on 3D Vision, 2019

2017

Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs.

Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Anisotropic Diffusion Descriptors.

Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers

Comput. Graph. Forum, 2016

Geometric deep learning.

Jonathan Masci, Emanuele Rodolà, Davide Boscaini, Michael M. Bronstein, Hao Li

Proceedings of the SIGGRAPH ASIA 2016, Macao, December 5-8, 2016 - Courses, 2016

Learning shape correspondence with anisotropic convolutional neural networks.

Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Deep Learning for Shape Analysis.

Michael M. Bronstein, Evangelos Kalogerakis, Emanuele Rodolà, Jonathan Masci, Davide Boscaini

Proceedings of the 37th Annual Conference of the European Association for Computer Graphics, 2016

2015

ShapeNet: Convolutional Neural Networks on Non-Euclidean Manifolds.

Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst

CoRR, 2015

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

Davide Boscaini, Jonathan Masci, Simone Melzi, Michael M. Bronstein, Umberto Castellani, Pierre Vandergheynst

Comput. Graph. Forum, 2015

Shape-from-Operator: Recovering Shapes from Intrinsic Operators.

Davide Boscaini, Davide Eynard, Drosos Kourounis, Michael M. Bronstein

Comput. Graph. Forum, 2015

Geodesic Convolutional Neural Networks on Riemannian Manifolds.

Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst

Proceedings of the 2015 IEEE International Conference on Computer Vision Workshop, 2015

2014

A sparse coding approach for local-to-global 3D shape description.

Davide Boscaini, Umberto Castellani

Vis. Comput., 2014

Shape-from-intrinsic operator.

Davide Boscaini, Davide Eynard, Michael M. Bronstein

CoRR, 2014

Coulomb Shapes: Using Electrostatic Forces for Deformation-invariant Shape Representation.

Davide Boscaini, Ramunas Girdziusas, Michael M. Bronstein

Proceedings of the 7th Eurographics Workshop on 3D Object Retrieval, 2014

2013

Local Signature Quantization by Sparse Coding.

Davide Boscaini, Umberto Castellani

Proceedings of the 6th Eurographics Workshop on 3D Object Retrieval, 2013