Abstract
Cross-spectral face recognition systems are designed to enhance the performance of facial recognition systems by enabling cross-modal matching under challenging operational conditions. A particularly relevant application is the matching of near-infrared (NIR) images to visible-spectrum (VIS) images, enabling the verification of individuals by comparing NIR facial captures acquired with VIS reference images. The use of NIR imaging offers several advantages, including greater robustness to illumination variations, better visibility through glasses and glare, and greater resistance to presentation attacks. Despite these claimed benefits, the robustness of NIR-based systems against presentation attacks has not been systematically studied in the literature. In this work, we conduct a comprehensive evaluation into the vulnerability of NIR-VIS cross-spectral face recognition systems to presentation attacks. Our empirical findings indicate that, although these systems exhibit a certain degree of reliability, they remain vulnerable to specific attacks, emphasizing the need for further research in this area.
Abstract (translated)
跨光谱人脸识别系统旨在通过启用在挑战性的操作条件下进行跨模态匹配，来增强面部识别系统的性能。一个特别相关的应用是将近红外（NIR）图像与可见光谱（VIS）图像进行匹配，使得可以通过比较从可见光谱参考图像中获取的近红外面部捕捉图像来验证个人身份。使用近红外成像提供了一些优势，包括更强的光照变化鲁棒性、更好的透过眼镜和眩光效果以及对呈现攻击更强的抵抗力。尽管这些系统声称具有诸多优点，但基于近红外的系统在面对呈现攻击时的鲁棒性的研究尚未在文献中得到系统的探讨。 在这项工作中，我们进行了全面评估跨光谱（NIR-VIS）人脸识别系统对于呈现攻击的脆弱性。我们的实证研究表明，虽然这些系统显示了一定程度上的可靠性，但它们仍然容易受到特定类型的攻击，这强调了在此领域进一步研究的需求。
URL
https://arxiv.org/abs/2505.00380
