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Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example

Abstract

While makeup virtual-try-on is now widespread, parametrizing a computer graphics rendering engine for synthesizing images of a given cosmetics product remains a challenging task. In this paper, we introduce an inverse computer graphics method for automatic makeup synthesis from a reference image, by learning a model that maps an example portrait image with makeup to the space of rendering parameters. This method can be used by artists to automatically create realistic virtual cosmetics image samples, or by consumers, to virtually try-on a makeup extracted from their favorite reference image.
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Dates and versions

hal-03261346 , version 1 (15-06-2021)

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Robin Kips, Ruowei Jiang, Sileye Ba, Edmund Phung, Parham Aarabi, et al.. Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example. CVPR Workshop Computer Vision for Fashion Art and Design, Jun 2021, Nashville (Virtual), United States. ⟨hal-03261346⟩
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