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English(EN) LAION-Mobile: Evaluating Deepfake Detectors On One Million Smartphone Photos

新数据集揭示深度伪造检测器在智能手机照片上失效

一项新的研究论文介绍了LAION-Mobile,一个包含一百万张智能手机图像的数据集,旨在评估深度伪造检测器。研究发现,在经过现代智能手机计算摄影管道处理的图像上,当前的检测器表现不佳,AUC得分低于0.624,有些甚至低于随机水平。此外,在旧数据上校准的阈值会导致真实智能手机照片的高误报率,表明现有检测器区分当前设备上真实和AI生成内容的能力存在显著差距。 AI

影响 凸显了深度伪造检测中的一个关键漏洞,可能影响内容真实性验证,并需要新的AI生成媒体方法。

排序理由 介绍新数据集和评估结果的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新数据集揭示深度伪造检测器在智能手机照片上失效

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介绍新数据集和评估结果的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Achim von Stryk, Janis Keuper ·

    LAION-Mobile:在一百万张智能手机照片上评估深度伪造检测器

    arXiv:2609.11134v1 Announce Type: new Abstract: Most Deepfake detectors report near-perfect AUC scores on their reference benchmarks. However, a recent ICML position paper argues that these evaluations collectively neglect the impact of modern smartphone photography: the widely u…