标题：稳定签名：潜在扩散模型中的生根水印
作者：Pierre Fernandez, Guillaume Couairon, Hervé Jégou, Matthijs Douze, Teddy Furon
文章链接：https://arxiv.org/abs/2303.15435
项目代码：https://pierrefdz.github.io/publications/stablesignature/
生成图像建模可实现广泛的应用，但会引发对负责任部署的伦理担忧。本文介绍了一种结合图像水印和潜在扩散模型的主动策略。目标是让所有生成的图像隐藏一个不可见的水印，以便将来检测和/或识别。该方法以二进制签名为条件，快速微调图像生成器的潜在解码器。
预先训练的水印提取器从任何生成的图像中恢复隐藏的签名，然后统计测试确定它是否来自生成模型。我们评估了水印在各种生成任务中的不可见性和稳健性，表明即使在图像被修改后，稳定签名也能正常工作。
例如，它检测从文本提示生成的图像的来源，然后裁剪以保留10%的内容， 90%+ 的准确度低于0.000001的误报率。
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