Knowledge Commons of Institute of Automation,CAS
Adversarial image generation by combining content and style | |
Liu, Songyan1,2; Zhao, Chaoyang1,2; Gao, Yunze1,2; Wang, Jinqiao1,2; Tang, Ming1,2 | |
发表期刊 | IET IMAGE PROCESSING |
ISSN | 1751-9659 |
2019-12-12 | |
卷号 | 13期号:14页码:2716-2723 |
摘要 | Images can be considered as the combination of two parts: the content and the style. The authors' approach can leverage this property by extracting a certain unique style from the reference images and combining it to generate images with new contents. With a well-defined style feature extraction module, they propose a novel framework to generate images with various styles and the same content. To train the style specific image generation model efficiently, a double-cycle training strategy is proposed: they input two natural-content pairs simultaneously, extract their style features, and exchange them twice to obtain the reconstruction of the input natural images. What is more, they apply the triplet margin loss to the style feature extracted from the images before and after style exchange and an adversarial discriminator to force the style-exchanged images to be real. They perform experiments on licence-plate image, Chinese characters, and shoes or handbags images generating, obtain photo-realistic results and remarkably improve the corresponding supervised recognition task. |
关键词 | image recognition feature extraction learning (artificial intelligence) image texture adversarial image generation unique style reference images style feature extraction module style specific image generation model double-cycle training strategy natural-content pairs input natural images style exchange style-exchanged images licence-plate image handbags images |
DOI | 10.1049/iet-ipr.2019.0103 |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering ; Imaging Science & Photographic Technology |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology |
WOS记录号 | WOS:000505048400008 |
出版者 | INST ENGINEERING TECHNOLOGY-IET |
七大方向——子方向分类 | 图像视频处理与分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/29474 |
专题 | 紫东太初大模型研究中心_图像与视频分析 |
通讯作者 | Zhao, Chaoyang |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Liu, Songyan,Zhao, Chaoyang,Gao, Yunze,et al. Adversarial image generation by combining content and style[J]. IET IMAGE PROCESSING,2019,13(14):2716-2723. |
APA | Liu, Songyan,Zhao, Chaoyang,Gao, Yunze,Wang, Jinqiao,&Tang, Ming.(2019).Adversarial image generation by combining content and style.IET IMAGE PROCESSING,13(14),2716-2723. |
MLA | Liu, Songyan,et al."Adversarial image generation by combining content and style".IET IMAGE PROCESSING 13.14(2019):2716-2723. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
IPR-2019-0103-FINAL.(4319KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论