Image-to-Image Translation: Methods and Applications

被引:187
作者
Pang, Yingxue [1 ]
Lin, Jianxin [2 ]
Qin, Tao [3 ]
Chen, Zhibo [1 ]
机构
[1] Univ Sci & Technol China, Dept Elect Engineer & Informat Sci, Hefei 230026, Anhui, Peoples R China
[2] Hunan Univ, Sch Comp Sci & Elect Engn, Changsha 410000, Peoples R China
[3] Microsoft Res Asia, Beijing 100080, Peoples R China
关键词
Task analysis; Data models; Generative adversarial networks; Measurement; Generators; PSNR; Analytical models; Image-to-image translation; two-domain I2I; multi-domain I2I; supervised methods; unsupersived methods; semi-supervised methods; few-shot methods; GENERATIVE ADVERSARIAL NETWORKS; SEMI; GAN;
D O I
10.1109/TMM.2021.3109419
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Image-to-image translation (I2I) aims to transfer images from a source domain to a target domain while preserving the content representations. I2I has drawn increasing attention and made tremendous progress in recent years because of its wide range of applications in many computer vision and image processing problems, such as image synthesis, segmentation, style transfer, restoration, and pose estimation. In this paper, we provide an overview of the I2I works developed in recent years. We will analyze the key techniques of the existing I2I works and clarify the main progress the community has made. Additionally, we will elaborate on the effect of I2I on the research and industry community and point out remaining challenges in related fields.
引用
收藏
页码:3859 / 3881
页数:23
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