Model and determine whether any of a user's face images is used in training the
Inference problem and propose a complete toolkit FACE-AUDITOR that canĬarefully choose the probing set to query the few-shot-based facial recognition In this paper, we formulate the auditing process as a user-level membership Not interfere with the facial recognition model's utility and cannot be quickly To prevent the face images from being misused, one straightforwardĪpproach is to modify the raw face images before sharing them, which inevitablyĭestroys the semantic information, increases the difficulty of retroactivity,Īnd is still prone to adaptive attacks. Well-performed facial recognition models without people's awareness andĬonsent. However, the power of facial recognition systemsĮnables entities with moderate resources to canvas the Internet and build Download a PDF of the paper titled FACE-AUDITOR: Data Auditing in Facial Recognition Systems, by Min Chen and Zhikun Zhang and Tianhao Wang and Michael Backes and Yang Zhang Download PDF Abstract: Few-shot-based facial recognition systems have gained increasing attentionĭue to their scalability and ability to work with a few face images during the
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