{"title":"迷人发型的建议","authors":"Yuto Nakamae, Xueting Wang, T. Yamasaki","doi":"10.1145/3379173.3393709","DOIUrl":null,"url":null,"abstract":"People change their hairstyles to make their appearance attractive, however it is difficult to determine which hairstyles are attractive. In this study, we aim to recommend a hairstyle that improves the attractiveness for an input face using attractiveness evaluation and image generation by deep learning. In the experiment, we first learned the attractiveness and obtained results similar to human intuition. Second, the hairstyle of the input image was changed using two methods: hairstyle attribute conversion and face swapping. Finally, a comparison experiment was performed by subjectively evaluating the input image and the image obtained by the proposed method. As a result, the proposed method was able to generate images with high evaluation value.","PeriodicalId":416027,"journal":{"name":"Proceedings of the 2020 Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Recommendations for Attractive Hairstyles\",\"authors\":\"Yuto Nakamae, Xueting Wang, T. Yamasaki\",\"doi\":\"10.1145/3379173.3393709\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"People change their hairstyles to make their appearance attractive, however it is difficult to determine which hairstyles are attractive. In this study, we aim to recommend a hairstyle that improves the attractiveness for an input face using attractiveness evaluation and image generation by deep learning. In the experiment, we first learned the attractiveness and obtained results similar to human intuition. Second, the hairstyle of the input image was changed using two methods: hairstyle attribute conversion and face swapping. Finally, a comparison experiment was performed by subjectively evaluating the input image and the image obtained by the proposed method. As a result, the proposed method was able to generate images with high evaluation value.\",\"PeriodicalId\":416027,\"journal\":{\"name\":\"Proceedings of the 2020 Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3379173.3393709\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3379173.3393709","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
People change their hairstyles to make their appearance attractive, however it is difficult to determine which hairstyles are attractive. In this study, we aim to recommend a hairstyle that improves the attractiveness for an input face using attractiveness evaluation and image generation by deep learning. In the experiment, we first learned the attractiveness and obtained results similar to human intuition. Second, the hairstyle of the input image was changed using two methods: hairstyle attribute conversion and face swapping. Finally, a comparison experiment was performed by subjectively evaluating the input image and the image obtained by the proposed method. As a result, the proposed method was able to generate images with high evaluation value.