3 citations · 15 across the 14 of their papers we have counts for
16 papers
RankAlign: Vision-Language Representation Alignment via Rank Transformation
Enzhe Zhao, Marco Fiorucci, Lamberto Ballan
While the Platonic Representation Hypothesis posits that vision and language models converge toward compatible latent geometries, recovering class-level correspondences between unp…
From Detection to Localization: A Unified Forensics Framework for Fully Synthetic and Tampered Images
Annalisa Gallina, Marco Fiorucci, Marco Brigo +2
The rapid advancement of generative models has significantly worsened the problem of manipulated image detection, as these methods are capable of producing highly realistic forgeri…
You Only Landmark Once: Lightweight U-Net Face Super Resolution with YOLO-World Landmark Heatmaps
Riccardo Carraro, Anna Briotto, Endi Hysa +2
Face image super-resolution aims to recover high-resolution facial images from severely degraded inputs. Under extreme upscaling factors, fine facial details are often lost, making…
Multiview Progress Prediction of Robot Activities
Elena Zoppellari, Federico Becattini, Marco Fiorucci +1
For robots to operate effectively and safely alongside humans, they must be able to understand the progress of ongoing actions. This ability, known as action progress prediction, i…
Impact of LiDAR visualisations on semantic segmentation of archaeological objects
Raveerat Jaturapitpornchai, Giulio Poggi, Gregory Sech +3
Deep learning methods in LiDAR-based archaeological research often leverage visualisation techniques derived from Digital Elevation Models to enhance characteristics of archaeologi…
Pansharpening of PRISMA products for archaeological prospection
Gregory Sech, Giulio Poggi, Marina Ljubenovic +2
Hyperspectral data recorded from satellite platforms are often ill-suited for geo-archaeological prospection due to low spatial resolution. The established potential of hyperspectr…
Implicit neural representation for change detection
Peter Naylor, Diego Di Carlo, Arianna Traviglia +2
Identifying changes in a pair of 3D aerial LiDAR point clouds, obtained during two distinct time periods over the same geographic region presents a significant challenge due to the…
Transfer Learning of Semantic Segmentation Methods for Identifying Buried Archaeological Structures on LiDAR Data
Gregory Sech, Paolo Soleni, Wouter B. Verschoof-van der Vaart +3
When applying deep learning to remote sensing data in archaeological research, a notable obstacle is the limited availability of suitable datasets for training models. The applicat…
Optimal Transport for Change Detection on LiDAR Point Clouds
Marco Fiorucci, Peter Naylor, Makoto Yamada
Unsupervised change detection between airborne LiDAR data points, taken at separate times over the same location, can be difficult due to unmatching spatial support and noise from…
Regular Partitions and Their Use in Structural Pattern Recognition
Marco Fiorucci
Recent years are characterized by an unprecedented quantity of available network data which are produced at an astonishing rate by an heterogeneous variety of interconnected sensor…
Separating Structure from Noise in Large Graphs Using the Regularity Lemma
Marco Fiorucci, Francesco Pelosin, Marcello Pelillo
How can we separate structural information from noise in large graphs? To address this fundamental question, we propose a graph summarization approach based on Szemerédi's Regulari…
Analysis of large sparse graphs using regular decomposition of graph distance matrices
Hannu Reittu, Lasse Leskelä, Tomi Räty +1
Statistical analysis of large and sparse graphs is a challenging problem in data science due to the high dimensionality and nonlinearity of the problem. This paper presents a fast…
On the Interplay between Strong Regularity and Graph Densification
Marco Fiorucci, Alessandro Torcinovich, Manuel Curado +2
In this paper we analyze the practical implications of Szemerédi's regularity lemma in the preservation of metric information contained in large graphs. To this end, we present a h…
Functional Dynamical Structures in Complex Systems: an Information-Theoretic Approach
Marco Fiorucci
Understanding the dynamical behavior of complex systems is of exceptional relevance in everyday life, from biology to economy. In order to describe the dynamical organization of co…
Revealing Structure in Large Graphs: Szemerédi's Regularity Lemma and its Use in Pattern Recognition
Marcello Pelillo, Ismail Elezi, Marco Fiorucci
Introduced in the mid-1970's as an intermediate step in proving a long-standing conjecture on arithmetic progressions, Szemerédi's regularity lemma has emerged over time as a funda…
The search for candidate relevant subsets of variables in complex systems
Marco Villani, Andrea Roli, Alessandro Filisetti +3
In this paper we describe a method to identify "relevant subsets" of variables, useful to understand the organization of a dynamical system. The variables belonging to a relevant s…