Denoised eye tracking heatmaps yield the largest generalization gain in open-set iris presentation attack detection, lowering APCER at 1% BPCER compared to cross-entropy training.
Benchmarking foundation models for zero-shot biometric tasks
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FPBench evaluates 20 MLLMs across 8 fingerprint tasks on 7 datasets and shows fine-tuning vision and language encoders improves performance by 7-39%.
Vision foundation models transfer across similar iris datasets but fail to generalize to unseen presentation attacks and cross-spectral shifts in open-set PAD.
citing papers explorer
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VISER: Visually-Informed System for Enhanced Robustness in Open-Set Iris Presentation Attack Detection
Denoised eye tracking heatmaps yield the largest generalization gain in open-set iris presentation attack detection, lowering APCER at 1% BPCER compared to cross-entropy training.
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FPBench: A Comprehensive Benchmark of Multimodal Large Language Models for Fingerprint Analysis
FPBench evaluates 20 MLLMs across 8 fingerprint tasks on 7 datasets and shows fine-tuning vision and language encoders improves performance by 7-39%.
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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.
- Compatibility of Face Embeddings Across Deep Neural Networks