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English(EN) Towards Zero-Shot Domain Generalization for ID Cards Presentation Attack Detection

新方法在身份证件攻击零样本检测中实现9%的EER

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种新颖的方法，用于身份证件呈现攻击检测（PAD）的零样本域泛化。该方法利用带有EfficientNet-V2-b0骨干网络的原型网络，每类仅需四个真实样本即可建立可靠的原型。通过改变卡片域而保持PAD类别不变的片段式训练机制，使网络能够学习通用的攻击线索。该系统在多国数据集和DLC-2021基准测试上实现了约9%的平均错误率（EER），优于现有基线，并实现了隐私保护、可扩展的跨司法管辖区远程注册。 AI

影响 这项研究通过实现更准确、更注重隐私的身份证件验证，有望提高远程注册流程的安全性和效率。

排序理由 该集群包含一篇详细介绍新的呈现攻击检测方法的学术论文。

在 arXiv cs.CV 阅读 →

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新方法在身份证件攻击零样本检测中实现9%的EER

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报道来源 [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    迈向零样本领域泛化用于身份证件呈现攻击检测

    Presentation-Attack Detection (PAD) for national ID cards is limited by the lack of publicly available genuine samples, making it difficult for systems to generalize across countries. This paper introduces two main innovations: (1) a Prototypical Network head using an EfficientNe…

  2. arXiv cs.CV TIER_1 English(EN) · Mario Nieto-Hidalgo, Juan M. Espin, Juan E. Tapia ·

    迈向零样本领域泛化用于身份证件呈现攻击检测

    arXiv:2608.16591v1 Announce Type: new Abstract: Presentation-Attack Detection (PAD) for national ID cards is limited by the lack of publicly available genuine samples, making it difficult for systems to generalize across countries. This paper introduces two main innovations: (1) …

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