{"title":"Deep learning method for makeup style transfer: A survey","authors":"Xiaohan Ma , Fengquan Zhang , Huan Wei , Liuqing Xu","doi":"10.1016/j.cogr.2021.09.001","DOIUrl":null,"url":null,"abstract":"<div><p>Makeup transfer is one of the applications of image style transfer, which refers to transfer the reference makeup to the face without makeup, and maintaining the original appearance of the plain face and the makeup style of the reference face. In order to understand the research status of makeup transfer, this paper systematically sorts out makeup transfer technology. According to the development process of the method of makeup transfer, our paper first introduces and analyzes the traditional methods of makeup transfer. In particular, the methods of makeup transfer based on deep learning framework are summarized, covering both disadvantages and advantages. Finally, some key points in the current challenges and future development direction of makeup transfer technology are discussed.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"1 ","pages":"Pages 182-187"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266724132100015X/pdfft?md5=c5178cad6941ffa98c8c774fb2ac3ca3&pid=1-s2.0-S266724132100015X-main.pdf","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Robotics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266724132100015X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Makeup transfer is one of the applications of image style transfer, which refers to transfer the reference makeup to the face without makeup, and maintaining the original appearance of the plain face and the makeup style of the reference face. In order to understand the research status of makeup transfer, this paper systematically sorts out makeup transfer technology. According to the development process of the method of makeup transfer, our paper first introduces and analyzes the traditional methods of makeup transfer. In particular, the methods of makeup transfer based on deep learning framework are summarized, covering both disadvantages and advantages. Finally, some key points in the current challenges and future development direction of makeup transfer technology are discussed.