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In this work we propose Identity Consistency Transformer, a novel faceforgery detection method that focuses on high-level semantics, specificallyidentity information, and detecting a suspect face by finding identityinconsistency in inner and outer face regions. The Identity ConsistencyTransformer incorporates a consistency loss for identity consistencydetermination. We show that Identity Consistency Transformer exhibits superiorgeneralization ability not only across different datasets but also acrossvarious types of image degradation forms found in real-world applicationsincluding deepfake videos. The Identity Consistency Transformer can be easilyenhanced with additional identity information when such information isavailable, and for this reason it is especially well-suited for detecting faceforgeries involving celebrities. Code will be released at\url{https://github.com/LightDXY/ICT_DeepFake}

Protecting Celebrities from DeepFake with Identity Consistency Transformer