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

Robin Kips, Ruowei Jiang, Sileye Ba, Edmund Phung, Parham Aarabi, Pietro Gori, Matthieu Perrot, Isabelle Bloch; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2021, pp. 3889-3893

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.

Related Material

[pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Kips_2021_CVPR, author = {Kips, Robin and Jiang, Ruowei and Ba, Sileye and Phung, Edmund and Aarabi, Parham and Gori, Pietro and Perrot, Matthieu and Bloch, Isabelle}, title = {Deep Graphics Encoder for Real-Time Video Makeup Synthesis From Example}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2021}, pages = {3889-3893} }