Vision foundation models transfer across similar iris datasets but fail to generalize to unseen presentation attacks and cross-spectral shifts in open-set PAD.
Information Tech- nology - Biometric presentation attack detection - Part 3: Testing and Reporting, International Organization for Standardization, 2017
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R-FLoRA combines Laplacian residual statistics with a frozen vision transformer via gated low-rank adapters, residual fusion, and contrastive alignment to achieve better accuracy and generalization than prior single-image face morphing attack detectors.
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A Systematic Failure Analysis of Vision Foundation Models for Open Set Iris Presentation Attack Detection
Vision foundation models transfer across similar iris datasets but fail to generalize to unseen presentation attacks and cross-spectral shifts in open-set PAD.
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R-FLoRA: Residual-Statistic-Gated Low-Rank Adaptation for Single-Image Face Morphing Attack Detection
R-FLoRA combines Laplacian residual statistics with a frozen vision transformer via gated low-rank adapters, residual fusion, and contrastive alignment to achieve better accuracy and generalization than prior single-image face morphing attack detectors.