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  A Hybrid Model for Identity Obfuscation by Face Replacement

Sun, Q., Tewari, A., Xu, W., Fritz, M., Theobalt, C., & Schiele, B. (2018). A Hybrid Model for Identity Obfuscation by Face Replacement. Retrieved from http://arxiv.org/abs/1804.04779.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-5E25-C Version Permalink: http://hdl.handle.net/21.11116/0000-0002-5E26-B
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 Creators:
Sun, Qianru1, Author              
Tewari, Ayush2, Author              
Xu, Weipeng2, Author              
Fritz, Mario1, Author              
Theobalt, Christian2, Author              
Schiele, Bernt1, Author              
Affiliations:
1Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society, ou_persistent22              
2Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              

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Free keywords: Computer Science, Computer Vision and Pattern Recognition, cs.CV,Computer Science, Cryptography and Security, cs.CR
 Abstract: As more and more personal photos are shared and tagged in social media, avoiding privacy risks such as unintended recognition becomes increasingly challenging. We propose a new hybrid approach to obfuscate identities in photos by head replacement. Our approach combines state of the art parametric face synthesis with latest advances in Generative Adversarial Networks (GAN) for data-driven image synthesis. On the one hand, the parametric part of our method gives us control over the facial parameters and allows for explicit manipulation of the identity. On the other hand, the data-driven aspects allow for adding fine details and overall realism as well as seamless blending into the scene context. In our experiments, we show highly realistic output of our system that improves over the previous state of the art in obfuscation rate while preserving a higher similarity to the original image content.

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Language(s): eng - English
 Dates: 2018-04-122018-07-242018
 Publication Status: Published online
 Pages: 22 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 1804.04779
URI: http://arxiv.org/abs/1804.04779
BibTex Citekey: Sun_arXiv1804.04779
 Degree: -

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