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Is there a study that face masking privacy? 


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Face masking privacy has been studied in several papers. Sun et al. propose an attack method against liveness detection by using a mask printed with a textured pattern, which can resist face extractors optimized for face occlusion . Zhao et al. analyze the privacy property of an elementary matrices masking-based protocol for face recognition and demonstrate that it does not hold privacy under their defined model . Another study evaluates the effectiveness of identity-masking algorithms based on Canny filters for interfering with identification while preserving facial actions . Wang et al. introduce a novel face privacy-enhancing framework that obfuscates stored faces to protect users' privacy while maintaining data utility . Finally, Wang et al. propose the FaceMAE framework, which considers face privacy and recognition performance simultaneously by using randomly masked face images for training and reconstruction .

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Yes, the paper discusses the privacy issues of public face datasets and proposes a novel framework called FaceMAE for privacy-preserving face recognition via masked autoencoders.
No, the provided paper does not specifically mention the term "face masking privacy." The paper focuses on a novel face privacy-enhancing framework by obfuscating stored faces to protect facial attributes while maintaining face identity.
The provided paper is about the effectiveness of identity-masking algorithms in interfering with identification and preserving facial actions. It does not specifically mention a study on face masking privacy.
Yes, the paper discusses a study on face masking privacy. It proposes a method using a mask printed with a textured pattern to resist face recognition algorithms optimized for face occlusion.
No, the provided paper does not study face masking privacy. The paper analyzes the privacy property of an elementary matrices masking-based PVC protocol for face recognition.

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