collaborators

6 papers

cs.CV2025

Deceptive Beauty: Evaluating the Impact of Beauty Filters on Deepfake and Morphing Attack Detection

Sara Concas, Simone Maurizio La Cava, Andrea Panzino +3

Digital beautification through social media filters has become increasingly popular, raising concerns about the reliability of facial images and videos and the effectiveness of aut…

cs.CV2025

Deep Data Hiding for ICAO-Compliant Face Images: A Survey

Jefferson David Rodriguez Chivata, Davide Ghiani, Simone Maurizio La Cava +4

ICAO-compliant facial images, initially designed for secure biometric passports, are increasingly becoming central to identity verification in a wide range of application contexts,…

cs.CV2025

Exploiting Multiple Representations: 3D Face Biometrics Fusion with Application to Surveillance

Simone Maurizio La Cava, Roberto Casula, Sara Concas +5

3D face reconstruction (3DFR) algorithms are based on specific assumptions tailored to the limits and characteristics of the different application scenarios. In this study, we inve…

cs.CV2025

Fragile Watermarking for Image Certification Using Deep Steganographic Embedding

Davide Ghiani, Jefferson David Rodriguez Chivata, Stefano Lilliu +5

Modern identity verification systems increasingly rely on facial images embedded in biometric documents such as electronic passports. To ensure global interoperability and security…

cs.CV2025

Improving fingerprint presentation attack detection by an approach integrated into the personal verification stage

Marco Micheletto, Giulia Orrù, Luca Ghiani +1

Presentation Attack Detection (PAD) systems are usually designed independently of the fingerprint verification system. While this can be acceptable for use cases where specific use…

cs.CR2024

Vulnerabilities in Machine Learning-Based Voice Disorder Detection Systems

Gianpaolo Perelli, Andrea Panzino, Roberto Casula +3

The impact of voice disorders is becoming more widely acknowledged as a public health issue. Several machine learning-based classifiers with the potential to identify disorders hav…