@inproceedings{2a513a4129064ebb9adcd789a2ed8dd0,
title = "Live face de-identification in video",
abstract = "We propose a method for face de-identification that enables fully automatic video modification at high frame rates. The goal is to maximally decorrelate the identity, while having the perception (pose, illumination and expression) fixed. We achieve this by a novel feed-forward encoder-decoder network architecture that is conditioned on the high-level representation of a person's facial image. The network is global, in the sense that it does not need to be retrained for a given video or for a given identity, and it creates natural looking image sequences with little distortion in time.",
author = "Oran Gafni and Lior Wolf and Yaniv Taigman",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 17th IEEE/CVF International Conference on Computer Vision, ICCV 2019 ; Conference date: 27-10-2019 Through 02-11-2019",
year = "2019",
month = oct,
doi = "10.1109/ICCV.2019.00947",
language = "الإنجليزيّة",
series = "Proceedings of the IEEE International Conference on Computer Vision",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "9377--9386",
booktitle = "Proceedings - 2019 International Conference on Computer Vision, ICCV 2019",
address = "الولايات المتّحدة",
}