Face photo-line drawings synthesis based on local extraction preserving generative adversarial networks

Yi Lihamu·Ya Ermaimaiti, Po Wang, Ying Tezhaer· Ai Shanjiang
{"title":"Face photo-line drawings synthesis based on local extraction preserving generative adversarial networks","authors":"Yi Lihamu·Ya Ermaimaiti, Po Wang, Ying Tezhaer· Ai Shanjiang","doi":"10.1080/13682199.2024.2315848","DOIUrl":null,"url":null,"abstract":"Facial photo-to-sketch synthesis is crucial for entertainment and criminal investigations, yet challenges persist, including local detail blurring and identity feature loss. To mitigate these probl...","PeriodicalId":22456,"journal":{"name":"The Imaging Science Journal","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Imaging Science Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/13682199.2024.2315848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Facial photo-to-sketch synthesis is crucial for entertainment and criminal investigations, yet challenges persist, including local detail blurring and identity feature loss. To mitigate these probl...
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于局部提取保存生成对抗网络的人脸照片线图合成
从面部照片到草图的合成对于娱乐和犯罪调查至关重要,但挑战依然存在,包括局部细节模糊和身份特征丢失。为了缓解这些问题,我们需要一种新的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Impact of the Internet of Medical Things on Artificial Intelligence-enhanced medical imaging systems from 2019 to 2023 Advancements in adversarial generative text-to-image models: a review Enhancing image encryption security through integration multi-chaotic systems and mixed pixel-bit level Unsupervised low-light image enhancement by data augmentation and contrastive learning Minimum error threshold segmentation method for SAR image based on Rayleigh distribution assumption
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1