4 papers
Sheaves Reloaded: A Directional Awakening
Stefano Fiorini, Hakan Aktas, Iulia Duta +4
Sheaf Neural Networks (SNNs) represent a powerful generalization of Graph Neural Networks (GNNs) that significantly improve our ability to model complex relational data. While dire…
Maps from Motion (MfM): Generating 2D Semantic Maps from Sparse Multi-view Images
Matteo Toso, Stefano Fiorini, Stuart James +1
World-wide detailed 2D maps require enormous collective efforts. OpenStreetMap is the result of 11 million registered users manually annotating the GPS location of over 1.75 billio…
Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving
Theodore Tsesmelis, Luca Palmieri, Marina Khoroshiltseva +20
This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dat…
Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs
Stefano Fiorini, Stefano Coniglio, Michele Ciavotta +1
We introduce QuaterGCN, a spectral Graph Convolutional Network (GCN) with quaternion-valued weights at whose core lies the Quaternionic Laplacian, a quaternion-valued Laplacian mat…