{"title":"一种基于变分自编码器的人脸融合方法","authors":"Xiang Li, Jinghao Wen, Anni Chen, Bo Chen","doi":"10.1109/ICCWAMTIP.2018.8632589","DOIUrl":null,"url":null,"abstract":"Face fusion refers to fuse two different facial images into a new face image that retains the facial features of the original image. Our network model is combine Variational Auto-Encoder(V Ae)and Generative Adversarial Networks(GAN), which achieved the end-to-end fusion task. Not only does it guarantee the quality of the fusion image(the image generated by GAN is sharp and photorealistic), but also doesn't lose specific details of the face(This is guaranteed by VAE). In the end, the experiment achieved a promising result on the CelebA dataset.","PeriodicalId":117919,"journal":{"name":"2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Method for Face Fusion Based on Variational Auto-Encoder\",\"authors\":\"Xiang Li, Jinghao Wen, Anni Chen, Bo Chen\",\"doi\":\"10.1109/ICCWAMTIP.2018.8632589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Face fusion refers to fuse two different facial images into a new face image that retains the facial features of the original image. Our network model is combine Variational Auto-Encoder(V Ae)and Generative Adversarial Networks(GAN), which achieved the end-to-end fusion task. Not only does it guarantee the quality of the fusion image(the image generated by GAN is sharp and photorealistic), but also doesn't lose specific details of the face(This is guaranteed by VAE). In the end, the experiment achieved a promising result on the CelebA dataset.\",\"PeriodicalId\":117919,\"journal\":{\"name\":\"2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCWAMTIP.2018.8632589\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCWAMTIP.2018.8632589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Method for Face Fusion Based on Variational Auto-Encoder
Face fusion refers to fuse two different facial images into a new face image that retains the facial features of the original image. Our network model is combine Variational Auto-Encoder(V Ae)and Generative Adversarial Networks(GAN), which achieved the end-to-end fusion task. Not only does it guarantee the quality of the fusion image(the image generated by GAN is sharp and photorealistic), but also doesn't lose specific details of the face(This is guaranteed by VAE). In the end, the experiment achieved a promising result on the CelebA dataset.