65 citations · 167 across the 10 of their papers we have counts for
11 papers
ICDAR 2025 Competition on FEw-Shot Text line segmentation of ancient handwritten documents (FEST)
Silvia Zottin, Axel De Nardin, Giuseppe Branca +2
Text line segmentation is a critical step in handwritten document image analysis. Segmenting text lines in historical handwritten documents, however, presents unique challenges due…
Augmented Reality in Cultural Heritage: A Dual-Model Pipeline for 3D Artwork Reconstruction
Daniele Pannone, Alessia Castronovo, Maurizio Mancini +5
This paper presents an innovative augmented reality pipeline tailored for museum environments, aimed at recognizing artworks and generating accurate 3D models from single images. B…
An Investigation of Ear-EEG Signals for a Novel Biometric Authentication System
Danilo Avola, Giancarlo Crocetti, Gian Luca Foresti +3
This work explores the feasibility of biometric authentication using EEG signals acquired through in-ear devices, commonly referred to as ear-EEG. Traditional EEG-based biometric s…
U-DIADS-Bib: a full and few-shot pixel-precise dataset for document layout analysis of ancient manuscripts
Silvia Zottin, Axel De Nardin, Emanuela Colombi +3
Document Layout Analysis, which is the task of identifying different semantic regions inside of a document page, is a subject of great interest for both computer scientists and hum…
Efficient few-shot learning for pixel-precise handwritten document layout analysis
Axel De Nardin, Silvia Zottin, Matteo Paier +3
Layout analysis is a task of uttermost importance in ancient handwritten document analysis and represents a fundamental step toward the simplification of subsequent tasks such as o…
Masked Transformer for image Anomaly Localization
Axel De Nardin, Pankaj Mishra, Gian Luca Foresti +1
Image anomaly detection consists in detecting images or image portions that are visually different from the majority of the samples in a dataset. The task is of practical importanc…
Drone swarm patrolling with uneven coverage requirements
Claudio Piciarelli, Gian Luca Foresti
Swarms of drones are being more and more used in many practical scenarios, such as surveillance, environmental monitoring, search and rescue in hardly-accessible areas, etc.. While…
VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization
Pankaj Mishra, Riccardo Verk, Daniele Fornasier +2
We present a transformer-based image anomaly detection and localization network. Our proposed model is a combination of a reconstruction-based approach and patch embedding. The use…
Image Anomaly Detection by Aggregating Deep Pyramidal Representations
Pankaj Mishra, Claudio Piciarelli, Gian Luca Foresti
Anomaly detection consists in identifying, within a dataset, those samples that significantly differ from the majority of the data, representing the normal class. It has many pract…
Image anomaly detection with capsule networks and imbalanced datasets
Claudio Piciarelli, Pankaj Mishra, Gian Luca Foresti
Image anomaly detection consists in finding images with anomalous, unusual patterns with respect to a set of normal data. Anomaly detection can be applied to several fields and has…
The UMCD Dataset
Danilo Avola, Gian Luca Foresti, Niki Martinel +2
In recent years, the technological improvements of low-cost small-scale Unmanned Aerial Vehicles (UAVs) are promoting an ever-increasing use of them in different tasks. In particul…