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This paper addresses the challenge of constructing a large-scale, high-quality synthetic face recognition dataset that contains no real-world identities, as required by the DataCV ICCV Face Recogni…
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This work introduces AirSignatureDB, a novel, publicly accessible dataset of in-air signature biometrics collected from 108 users in unconstrained real-world conditions using 83 different smartphon…
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This paper addresses the escalating threats to personal digital identity posed by generative AI technologies, including unauthorized cloning, impersonation, and monetization of digital likeness att…
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This paper addresses the challenge of deploying Physically Unclonable Functions (PUFs) for secure authentication in blockchain systems without relying on specialized hardware
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This paper investigates biometric verification in photorealistic talking-head avatar videos, where attackers may perform impersonation attacks by stealing a victim's avatar to replicate their appea…
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This paper investigates a fundamental and longstanding challenge in AI known as Moravec's paradox, specifically within the domain of auditory perception
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The paper asks whether phishing generation can be pushed beyond static, prompt-based output by treating attack design as an evolutionary process
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This paper tackles a practical but underexplored anti-cheating problem: detecting LLM-assisted writing in Korean from typing behavior rather than submitted text
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SynPAIN tackles a very specific but important data problem in automated pain assessment: most public facial-pain datasets are small, skew younger, and underrepresent the older adults and demographi…
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Vec2Face+ is a synthetic face-dataset generation method aimed at face recognition training, with the central claim that the remaining gap between synthetic and real training data is not just about …
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MFAz tackles a gap that standard access control and MFA do not address: once a session is already established, an attacker who steals or reuses the session identifier can often bypass the original …
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This paper studies whether the abstract facial-motion streams produced by mixed-reality headsets are privacy-sensitive behavioral biometrics, even when no raw video is exposed
