Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example
This addresses the problem of automating makeup virtual-try-on for artists and consumers, though it appears incremental as it builds on existing inverse graphics and virtual-try-on methods.
The paper tackles the challenge of parametrizing a rendering engine for makeup synthesis by introducing an inverse graphics method that maps a reference makeup image to rendering parameters, enabling automatic creation of realistic virtual cosmetics samples for artists and consumers.
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.