7 citations · 11 across the 12 of their papers we have counts for
6 papers · 1 filter
ONOT: a High-Quality ICAO-compliant Synthetic Mugshot Dataset
Nicolò Di Domenico, Guido Borghi, Annalisa Franco +1
Nowadays, state-of-the-art AI-based generative models represent a viable solution to overcome privacy issues and biases in the collection of datasets containing personal informatio…
Dealing with Subject Similarity in Differential Morphing Attack Detection
Nicolò Di Domenico, Guido Borghi, Annalisa Franco +1
The advent of morphing attacks has posed significant security concerns for automated Face Recognition systems, raising the pressing need for robust and effective Morphing Attack De…
V-MAD: Video-based Morphing Attack Detection in Operational Scenarios
Guido Borghi, Annalisa Franco, Nicolò Di Domenico +2
In response to the rising threat of the face morphing attack, this paper introduces and explores the potential of Video-based Morphing Attack Detection (V-MAD) systems in real-worl…
SDFR: Synthetic Data for Face Recognition Competition
Hatef Otroshi Shahreza, Christophe Ecabert, Anjith George +25
Large-scale face recognition datasets are collected by crawling the Internet and without individuals' consent, raising legal, ethical, and privacy concerns. With the recent advance…
Detecting Morphing Attacks via Continual Incremental Training
Lorenzo Pellegrini, Guido Borghi, Annalisa Franco +1
Scenarios in which restrictions in data transfer and storage limit the possibility to compose a single dataset -- also exploiting different data sources -- to perform a batch-based…
On the challenges to learn from Natural Data Streams
Guido Borghi, Gabriele Graffieti, Davide Maltoni
In real-world contexts, sometimes data are available in form of Natural Data Streams, i.e. data characterized by a streaming nature, unbalanced distribution, data drift over a long…