论文标题
通过身份一致性变压器保护名人免受深层影响
Protecting Celebrities from DeepFake with Identity Consistency Transformer
论文作者
论文摘要
在这项工作中，我们提出了身份一致性变压器，这是一种新型的面部伪造方法，重点是高级语义，特别是身份信息，并通过在内部和外部面积中发现身份不一致来检测可疑的面孔。身份一致性变压器结合了身份一致性确定的一致性损失。我们表明，身份一致性变压器不仅在不同的数据集中表现出卓越的概括能力，而且在包括DeepFake视频在内的真实世界应用程序中发现的各种类型的图像降解形式中都具有出色的概括能力。当可用的信息可用时，可以通过其他身份信息轻松增强身份一致性变压器，因此，它特别适合检测涉及名人的面部伪装。代码将在\ url {https://github.com/lightdxy/ict_deepfake}发布
In this work we propose Identity Consistency Transformer, a novel face forgery detection method that focuses on high-level semantics, specifically identity information, and detecting a suspect face by finding identity inconsistency in inner and outer face regions. The Identity Consistency Transformer incorporates a consistency loss for identity consistency determination. We show that Identity Consistency Transformer exhibits superior generalization ability not only across different datasets but also across various types of image degradation forms found in real-world applications including deepfake videos. The Identity Consistency Transformer can be easily enhanced with additional identity information when such information is available, and for this reason it is especially well-suited for detecting face forgeries involving celebrities. Code will be released at \url{https://github.com/LightDXY/ICT_DeepFake}
