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CVPR2024Top-tier venue

Selective, Interpretable and Motion Consistent Privacy Attribute Obfuscation for Action Recognition

Filip Ilic, He Zhao, Thomas Pock, Richard P. Wildes

2024Year
4Top-tier citations

Abstract

Figure 1 . Our goal is to hide privacy attributes without action recognition performance dropping. Left: Arbitrary images can be used to specify an interpretable template library defined by privacy attributes. Middle: A salience map is generated from privacy templates; example illustrates use of templates for personal identification. Right: The source video is masked with noise as guided by salience and animated by source video optical flow. Salience makes masking selective to privacy sensitive regions, while preserving scene context; optical flow preserves motion -both of which are critical for action recognition. The obfuscated video can be input directly to arbitrary privacy and action recognition systems without retraining. Zoomed circles highlight details only for illustration.

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