计算机应用研究2023，Vol.40Issue(12)：3854-3858,5.DOI:10.19734/j.issn.1001-3695.2023.05.0226
基于双流循环映射网络的肖像漫画化
Portrait caricature based on double-stream cycle mapping network
摘要
Abstract
Portrait artistic style transfer aims to transfer the style from a given reference artistic portrait painting to a portrait photo while preserving the basic semantic structure of the person's face.However,due to the sensitivity of the human visual system to the facial structure of person,the task of artistic style transfer of portraits is often more challenging than that for ge-neral image,especially for caricature type which with more abstract style elements.Existing image style transfer methods,which do not consider the abstraction of the caricature style and the preservation of basic semantic structure of the portrait face,often suffer from serious structural collapse and feature information confusion when applied to the portrait caricature task.To address this problem,this paper proposed a double-stream cycle mapping DSCM(double-stream cycle mapping network)network to portrait caricature.Firstly,based on BeautyGAN,it introduced a structural consistency loss and cooperating with the cycle con-sistency loss to maintain the integrity of the overall semantic structure of the portrait.Secondly,it designed a feature encoder combined with U2-Net to capture more valuable feature information of input images at different scales.In addition,it further in-troduced a style discriminator to discriminate the encoded style features to assist the network in learning abstract caricature style features closer to the target image.The experiments conducted qualitative comparisons of five advanced methods,and quantitative comparisons of FID(Fréchet inception distance)and PSNR(peak signal to noise ratio)index scores.The experi-mental results show that this method is superior to other methods.Through extensive experimental verification,the portrait cari-cature obtained by this method not only maintains the overall structure of the portrait and the basic semantic structure of the face,but also fully learns the abstract style of caricature.关键词
双流循坏映射网络/U2-Net/结构一致性损失/肖像漫画化/风格鉴别器Key words
double-stream cycle mapping network/U2-Net/structure consistency loss/portrait caricature/style discrimi-nator分类
信息技术与安全科学引用本文复制引用
孔凡敏,普园媛,赵征鹏,邓鑫,阳秋霞..基于双流循环映射网络的肖像漫画化[J].计算机应用研究,2023,40(12):3854-3858,5.基金项目
国家自然科学基金资助项目(62162068,61271361,61761046,62061049) （62162068,61271361,61761046,62061049）
云南省应用基础研究面上项目(2018FB100) （2018FB100）
云南省科技厅应用基础研究计划重点项目(202001BB050043,2019FA044) （202001BB050043,2019FA044）
