ID-Guard : A Universal Framework for Combating Facial Manipulation via Breaking Identification

The misuse of deep learning-based facial manipulation poses a serious threat to civil rights. To prevent such fraud at its source, proactive defense methods have been proposed that embed invisible adversarial perturbations into images, disrupting the manipulation process and rendering the forged out...

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Publié dans:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2025) vom: 01. Okt.
Auteur principal:	Qu, Zuomin (Auteur)
Autres auteurs:	Lu, Wei, Luo, Xiangyang, Wang, Qian, Cao, Xiaochun
Format:	Article en ligne
Langue:	English
Publié:	2025
Accès à la collection:	IEEE transactions on pattern analysis and machine intelligence
Sujets:	Journal Article