| 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 | 2570 | 2017 |
| 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 | 992 | 2015 |
| 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 | 950 | 2020 |
| Learning shape correspondence with anisotropic convolutional neural networks D Boscaini, J Masci, E Rodolà, M Bronstein Advances in neural information processing systems 29, 2016 | 660 | 2016 |
| 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 | 264 | 2015 |
| Anisotropic diffusion descriptors D Boscaini, J Masci, E Rodolà, MM Bronstein, D Cremers Computer Graphics Forum 35 (2), 431-441, 2016 | 150 | 2016 |
| 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 | 134 | 2022 |
| Distinctive 3D local deep descriptors F Poiesi, D Boscaini 2020 25th International conference on pattern recognition (ICPR), 5720-5727, 2021 | 70 | 2021 |
| Shapenet: Convolutional neural networks on non-euclidean manifolds J Masci, D Boscaini, MM Bronstein, P Vandergheynst CoRR, abs/1501.06297 3, 2015 | 70 | 2015 |
| Geometric deep learning J Masci, E Rodolà, D Boscaini, MM Bronstein, H Li SIGGRAPH ASIA 2016 Courses, 1-50, 2016 | 63 | 2016 |
| 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 | 54* | 2024 |
| Shape‐from‐operator: Recovering shapes from intrinsic operators D Boscaini, D Eynard, D Kourounis, MM Bronstein Computer Graphics Forum 34 (2), 265-274, 2015 | 50 | 2015 |
| 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 | 42 | 2021 |
| 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 | 25 | 2020 |
| Open-vocabulary object 6D pose estimation J Corsetti, D Boscaini, C Oh, A Cavallaro, F Poiesi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 22 | 2024 |
| 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 | 13 | 2023 |
| 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 | 13 | 2023 |
| 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 | 11 | 2023 |
| PatchMixer: Rethinking network design to boost generalization for 3D point cloud understanding D Boscaini, F Poiesi Image and vision computing 137, 104768, 2023 | 9 | 2023 |
| Supervised tractogram filtering using geometric deep learning P Astolfi, R Verhagen, L Petit, E Olivetti, S Sarubbo, J Masci, D Boscaini, ... Medical Image Analysis 90, 102893, 2023 | 8 | 2023 |
Michael BronsteinDeepMind Professor of AI, University of Oxford / Scientific Director, AITHYRAVerified email at cs.ox.ac.uk
