---
title: "Makeup Like a Superstar: Deep Localized Makeup Transfer Network"
authors:
  - "Si Liu"
  - "Xinyu Ou"
  - "Ruihe Qian"
  - "Wei Wang"
  - "Xiaochun Cao"
doi: ""
url: "https://ijcai.org/proceedings/2016/365"
pdf: "https://ijcai.org/proceedings/2016/0365.pdf"
venue: "Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence"
year: 2016
pages: "2568-2574"
track: ""
keywords:
---

# Makeup Like a Superstar: Deep Localized Makeup Transfer Network

Si Liu, Xinyu Ou, Ruihe Qian, Wei Wang, Xiaochun Cao

*Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence*, pages 2568-2574.

## Abstract

In this paper, we propose a novel Deep Localized Makeup Transfer Network to automatically recommend the most suitable makeup for a female and synthesis the makeup on her face. Given a before-makeup face, her most suitable makeup is determined automatically. Then, both the before makeup and the reference faces are fed into the proposed Deep Transfer Network to generate the after-makeup face. Our end-to-end makeup transfer network have several nice properties including: (1) with complete functions: including foundation, lip gloss, and eye shadow transfer; (2) cosmetic specific: different cosmetics are transferred in different manners; (3) localized: different cosmetics are applied on different facial regions; (4) producing naturally looking results without obvious artifacts; (5) controllable makeup lightness: various results from light makeup to heavy makeup can be generated. Qualitative and quantitative experiments show that our network performs much better than the methods of [Guo and Sim, 2009] and two variants of NerualStyle [Gatys et al., 2015a].