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20192026
most citedFace morphing detection in the presence of printing/scanning and heterogeneous image sources

39 citations · 84 across the 10 of their papers we have counts for

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9 papers · 1 filter

cs.CV2026

Arc2Morph: Identity-Preserving Facial Morphing with Arc2Face

Nicolò Di Domenico, Annalisa Franco, Matteo Ferrara +1

Face morphing attacks are widely recognized as one of the most challenging threats to face recognition systems used in electronic identity documents. These attacks exploit a critic…

cs.CV2025

Detecting Localized Deepfakes: How Well Do Synthetic Image Detectors Handle Inpainting?

Serafino Pandolfini, Lorenzo Pellegrini, Matteo Ferrara +1

The rapid progress of generative AI has enabled highly realistic image manipulations, including inpainting and region-level editing. These approaches preserve most of the original…

cs.CV2025

Generalized Design Choices for Deepfake Detectors

Lorenzo Pellegrini, Serafino Pandolfini, Davide Maltoni +3

The effectiveness of deepfake detection methods often depends less on their core design and more on implementation details such as data preprocessing, augmentation strategies, and…

cs.CV2025★ 2 cited

AI-GenBench: A New Ongoing Benchmark for AI-Generated Image Detection

Lorenzo Pellegrini, Davide Cozzolino, Serafino Pandolfini +5

The rapid advancement of generative AI has revolutionized image creation, enabling high-quality synthesis from text prompts while raising critical challenges for media authenticity…

cs.CV2025

From Gaming to Research: GTA V for Synthetic Data Generation for Robotics and Navigations

Matteo Scucchia, Matteo Ferrara, Davide Maltoni

In computer vision, the development of robust algorithms capable of generalizing effectively in real-world scenarios more and more often requires large-scale datasets collected und…

cs.CV2024

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…

cs.CV2022★ 29 cited

Morphing Attack Potential

Matteo Ferrara, Annalisa Franco, Davide Maltoni +1

In security systems the risk assessment in the sense of common criteria testing is a very relevant topic; this requires quantifying the attack potential in terms of the expertise o…

cs.CV2020★ 8 cited

Morphing Attack Detection -- Database, Evaluation Platform and Benchmarking

Kiran Raja, Matteo Ferrara, Annalisa Franco +18

Morphing attacks have posed a severe threat to Face Recognition System (FRS). Despite the number of advancements reported in recent works, we note serious open issues such as indep…

cs.CV2019★ 39 cited

Face morphing detection in the presence of printing/scanning and heterogeneous image sources

Matteo Ferrara, Annalisa Franco, Davide Maltoni

Face morphing represents nowadays a big security threat in the context of electronic identity documents as well as an interesting challenge for researchers in the field of face rec…