Makeup like a superstar: Deep Localized Makeup Transfer Network

Understand

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 beforemakeup 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.