7 citations · 11 across the 5 of their papers we have counts for
5 papers
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…
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…