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- W2953354721 abstract "Images convey a broad spectrum of personal information. If such images are shared on social media platforms, this personal information is leaked which conflicts with the privacy of depicted persons. Therefore, we aim for automated approaches to redact such private information and thereby protect privacy of the individual. By conducting a user study we find that obfuscating the image regions related to the private information leads to privacy while retaining utility of the images. Moreover, by varying the size of the regions different privacy-utility trade-offs can be achieved. Our findings argue for a by segmentation paradigm. Hence, we propose the first sizable dataset of private images in the wild annotated with pixel and instance level labels across a broad range of privacy classes. We present the first model for automatic redaction of diverse private information." @default.
- W2953354721 created "2019-06-27" @default.
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- W2953354721 date "2017-12-04" @default.
- W2953354721 modified "2023-09-27" @default.
- W2953354721 title "Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images" @default.
- W2953354721 hasPublicationYear "2017" @default.
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