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Natural and Effective Obfuscation by Head Inpainting

conference contribution
posted on 2023-11-29, 18:08 authored by Qianru Sun, Liqian Ma, Seong Joon Oh, Luc Van Gool, Bernt Schiele, Mario FritzMario Fritz
As more and more personal photos are shared online, being able to obfuscate identities in such photos is becoming a necessity for privacy protection. People have largely resorted to blacking out or blurring head regions, but they result in poor user experience while being surprisingly ineffective against state of the art person recognizers[17]. In this work, we propose a novel head inpainting obfuscation technique. Generating a realistic head inpainting in social media photos is challenging because subjects appear in diverse activities and head orientations. We thus split the task into two sub-tasks: (1) facial landmark generation from image context (e.g. body pose) for seamless hypothesis of sensible head pose, and (2) facial landmark conditioned head inpainting. We verify that our inpainting method generates realistic person images, while achieving superior obfuscation performance against automatic person recognizers.

History

Preferred Citation

Qianru Sun, Liqian Ma, Seong Oh, Luc Gool, Bernt Schiele and Mario Fritz. Natural and Effective Obfuscation by Head Inpainting. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2018.

Primary Research Area

  • Trustworthy Information Processing

Name of Conference

IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Legacy Posted Date

2018-05-04

Open Access Type

  • Gold

BibTeX

@inproceedings{cispa_all_2599, title = "Natural and Effective Obfuscation by Head Inpainting", author = "Sun, Qianru and Ma, Liqian and Oh, Seong Joon and Gool, Luc Van and Schiele, Bernt and Fritz, Mario", booktitle="{IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}", year="2018", }

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