Journal
IEEE TRANSACTIONS ON MULTIMEDIA
Volume 24, Issue -, Pages 3859-3881Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMM.2021.3109419
Keywords
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
Categories
Funding
- NSFC [U1908209, 61632001, 62021001]
- National Key Research and Development Program of China [2018AAA0101400]
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This paper provides an overview of recent developments in image-to-image translation (I2I), analyzing the key techniques and progress made in the field. It discusses the impact of I2I on research and industry, as well as the remaining challenges in related fields.
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.
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