39 citations · 117 across the 10 of their papers we have counts for
18 papers
Rethinking the compositionality of point clouds through regularization in the hyperbolic space
Antonio Montanaro, Diego Valsesia, Enrico Magli
Point clouds of 3D objects exhibit an inherent compositional nature where simple parts can be assembled into progressively more complex shapes to form whole objects. Explicitly cap…
Cross-modal Learning for Image-Guided Point Cloud Shape Completion
Emanuele Aiello, Diego Valsesia, Enrico Magli
In this paper we explore the recent topic of point cloud completion, guided by an auxiliary image. We show how it is possible to effectively combine the information from the two mo…
Super-resolved multi-temporal segmentation with deep permutation-invariant networks
Diego Valsesia, Enrico Magli
Multi-image super-resolution from multi-temporal satellite acquisitions of a scene has recently enjoyed great success thanks to new deep learning models. In this paper, we go beyon…
Denoise and Contrast for Category Agnostic Shape Completion
Antonio Alliegro, Diego Valsesia, Giulia Fracastoro +2
In this paper, we present a deep learning model that exploits the power of self-supervision to perform 3D point cloud completion, estimating the missing part and a context region a…
RAN-GNNs: breaking the capacity limits of graph neural networks
Diego Valsesia, Giulia Fracastoro, Enrico Magli
Graph neural networks have become a staple in problems addressing learning and analysis of data defined over graphs. However, several results suggest an inherent difficulty in extr…
Deep Learning Methods For Synthetic Aperture Radar Image Despeckling: An Overview Of Trends And Perspectives
Giulia Fracastoro, Enrico Magli, Giovanni Poggi +3
Synthetic aperture radar (SAR) images are affected by a spatially-correlated and signal-dependent noise called speckle, which is very severe and may hinder image exploitation. Desp…