Learning localized generative models for 3d point clouds via graph convolution D Valsesia, G Fracastoro, E Magli International conference on learning representations, 2018 | 201 | 2018 |
Deep graph-convolutional image denoising D Valsesia, G Fracastoro, E Magli IEEE Transactions on Image Processing 29, 8226-8237, 2020 | 178 | 2020 |
Deepsum: Deep neural network for super-resolution of unregistered multitemporal images AB Molini, D Valsesia, G Fracastoro, E Magli IEEE Transactions on Geoscience and Remote Sensing 58 (5), 3644-3656, 2019 | 165 | 2019 |
Speckle2Void: Deep self-supervised SAR despeckling with blind-spot convolutional neural networks AB Molini, D Valsesia, G Fracastoro, E Magli IEEE Transactions on Geoscience and Remote Sensing 60, 1-17, 2021 | 126 | 2021 |
Compressed fingerprint matching and camera identification via random projections D Valsesia, G Coluccia, T Bianchi, E Magli IEEE Transactions on Information Forensics and Security 10 (7), 1472-1485, 2015 | 106 | 2015 |
Learning graph-convolutional representations for point cloud denoising F Pistilli, G Fracastoro, D Valsesia, E Magli European conference on computer vision, 103-118, 2020 | 94 | 2020 |
Deep learning methods for synthetic aperture radar image despeckling: An overview of trends and perspectives G Fracastoro, E Magli, G Poggi, G Scarpa, D Valsesia, L Verdoliva IEEE Geoscience and Remote Sensing Magazine 9 (2), 29-51, 2021 | 74 | 2021 |
A novel rate control algorithm for onboard predictive coding of multispectral and hyperspectral images D Valsesia, E Magli IEEE Transactions on Geoscience and Remote Sensing 52 (10), 6341-6355, 2014 | 70 | 2014 |
Image Denoising with Graph-Convolutional Neural Networks D Valsesia, G Fracastoro, E Magli 2019 IEEE International Conference on Image Processing (ICIP), 2399-2403, 2019 | 65 | 2019 |
User authentication via PRNU-based physical unclonable functions D Valsesia, G Coluccia, T Bianchi, E Magli IEEE Transactions on Information Forensics and Security 12 (8), 1941-1956, 2017 | 65 | 2017 |
High-throughput onboard hyperspectral image compression with ground-based CNN reconstruction D Valsesia, E Magli IEEE transactions on geoscience and remote sensing 57 (12), 9544-9553, 2019 | 50 | 2019 |
Permutation invariance and uncertainty in multitemporal image super-resolution D Valsesia, E Magli IEEE Transactions on Geoscience and Remote Sensing 60, 1-12, 2021 | 47 | 2021 |
Denoise and contrast for category agnostic shape completion A Alliegro, D Valsesia, G Fracastoro, E Magli, T Tommasi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 42 | 2021 |
Large-scale image retrieval based on compressed camera identification D Valsesia, G Coluccia, T Bianchi, E Magli IEEE Transactions on Multimedia 17 (9), 1439-1449, 2015 | 42 | 2015 |
Learning robust graph-convolutional representations for point cloud denoising F Pistilli, G Fracastoro, D Valsesia, E Magli IEEE Journal of Selected Topics in Signal Processing 15 (2), 402-414, 2020 | 41 | 2020 |
Learning localized representations of point clouds with graph-convolutional generative adversarial networks D Valsesia, G Fracastoro, E Magli IEEE Transactions on Multimedia 23, 402-414, 2020 | 40 | 2020 |
Sampling of graph signals via randomized local aggregations D Valsesia, G Fracastoro, E Magli IEEE Transactions on Signal and Information Processing over Networks 5 (2 …, 2018 | 35 | 2018 |
Fast and lightweight rate control for onboard predictive coding of hyperspectral images D Valsesia, E Magli IEEE Geoscience and Remote Sensing Letters 14 (3), 394-398, 2017 | 35 | 2017 |
Rethinking the compositionality of point clouds through regularization in the hyperbolic space A Montanaro, D Valsesia, E Magli Advances in Neural Information Processing Systems 35, 33741-33753, 2022 | 34 | 2022 |
Cross-modal learning for image-guided point cloud shape completion E Aiello, D Valsesia, E Magli Advances in Neural Information Processing Systems 35, 37349-37362, 2022 | 30 | 2022 |