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.
arXiv preprint arXiv:2505.24214 (2025) 1, 3
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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.
Simple affine transformations align face embeddings across different DNN models, substantially improving cross-model identification and verification performance.
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.
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Are Face Embeddings Compatible Across Deep Neural Network Models?
Simple affine transformations align face embeddings across different DNN models, substantially improving cross-model identification and verification performance.