A Generative Adversarial Network for Multistyle Unsupervised Image Transfer Based on Dynamic Position Normalization

A Generative Adversarial Network for Multistyle Unsupervised Image Transfer Based on Dynamic Position Normalization

Image transfer is a technology that changes the image effect by processing the image’s color, contour, line, and other information. To stylize the visual appearance of the output will be adapted to the subject of the original image, this paper proposes an image feature transfer method cal...

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Bibliographic Details
Main Authors: Xiaodi Rang, Chaoqing Ma, Qiang Zheng, Guangzhi Zhao
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
CycleGAN
deep learning
generative adversarial network
image transfer
Online Access:https://ieeexplore.ieee.org/document/9881493/

Internet

https://ieeexplore.ieee.org/document/9881493/

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