  From TV news to Google StreetView, face obscuration has been used for privacy
protection. Due to recent advances in the field of deep learning, obscuration
methods such as Gaussian blurring and pixelation are not guaranteed to conceal
identity. In this paper, we propose a utility-preserving generative model,
UP-GAN, that is able to provide an effective face obscuration, while preserving
facial utility. By utility-preserving we mean preserving facial features that
do not reveal identity, such as age, gender, skin tone, pose, and expression.
We show that the proposed method achieves the best performance in terms of
obscuration and utility preservation.
