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cs.CV2026

Have I Seen You? Embedding Behavior Signals Synthetic Face Dataset Membership

Paweł Borsukiewicz, Daniele Lunghi, Wendkûuni C. Ouédraogo +2

Synthetic face datasets are increasingly used to reduce privacy exposure and data access constraints in biometric recognition. Yet the generators that produce these datasets are tr…

cs.CV2026

Benchmarking Face Recognition without Real Faces

Paweł Borsukiewicz, Daniele Lunghi, Wendkûuni C. Ouédraogo +2

The paper evaluates whether synthetic face datasets can replace real‑face benchmarks for assessing face recognition models, finding that the best synthetic sets achieve comparable…

cs.CV2026

Adversarial Camouflage

Paweł Borsukiewicz, Daniele Lunghi, Melissa Tessa +2

While the rapid development of facial recognition algorithms has enabled numerous beneficial applications, their widespread deployment has raised significant concerns about the ris…

cs.CV2025

Beyond Real Faces: Synthetic Datasets Can Achieve Reliable Recognition Performance without Privacy Compromise

Paweł Borsukiewicz, Fadi Boutros, Iyiola E. Olatunji +4

The deployment of facial recognition systems has created an ethical dilemma: achieving high accuracy requires massive datasets of real faces collected without consent, leading to d…

cs.CV2025

Explainable AI for Analyzing Person-Specific Patterns in Facial Recognition Tasks

Paweł Jakub Borsukiewicz, Jordan Samhi, Jacques Klein +1

The proliferation of facial recognition systems presents major privacy risks, driving the need for effective countermeasures. Current adversarial techniques apply generalized metho…