We show that even when face images are unconstrained and arbitrarily paired, face swapping between them is quite simple. To this end, we make the following contributions. (a) Instead of tailoring systems for face segmentation, as others previously proposed, we show that a standard fully convolutional network (FCN) can achieve remarkably fast and accurate segmentations, provided that it is trained on a rich enough example set. For this purpose, we describe novel data collection and generation routines which provide challenging segmented face examples. (b) We use our segmentations for robust face swapping under unprecedented conditions. (c) Unlike previous work, our swapping is robust enough to allow for extensive quantitative tests. To this end, we use the Labeled Faces in the Wild (LFW) benchmark and measure the effect of intra- and inter-subject face swapping on recognition.

On Face Segmentation, Face Swapping, and Face Perception / Nirkin, Yuval; Masi, I; Tran Anh, Tuan; Hassner, Tal; Medioni, Gerard. - (2018). (Intervento presentato al convegno IEEE Conference on Automatic Face and Gesture Recognition (FG) tenutosi a Xian (China)).

On Face Segmentation, Face Swapping, and Face Perception

Masi I;
2018

Abstract

We show that even when face images are unconstrained and arbitrarily paired, face swapping between them is quite simple. To this end, we make the following contributions. (a) Instead of tailoring systems for face segmentation, as others previously proposed, we show that a standard fully convolutional network (FCN) can achieve remarkably fast and accurate segmentations, provided that it is trained on a rich enough example set. For this purpose, we describe novel data collection and generation routines which provide challenging segmented face examples. (b) We use our segmentations for robust face swapping under unprecedented conditions. (c) Unlike previous work, our swapping is robust enough to allow for extensive quantitative tests. To this end, we use the Labeled Faces in the Wild (LFW) benchmark and measure the effect of intra- and inter-subject face swapping on recognition.
2018
IEEE Conference on Automatic Face and Gesture Recognition (FG)
face swapping, deep learning, face analysis
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
On Face Segmentation, Face Swapping, and Face Perception / Nirkin, Yuval; Masi, I; Tran Anh, Tuan; Hassner, Tal; Medioni, Gerard. - (2018). (Intervento presentato al convegno IEEE Conference on Automatic Face and Gesture Recognition (FG) tenutosi a Xian (China)).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1458944
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