Research on Ethnic Pattern Generation Based on Generative Adversarial Networks

被引:0
|
作者
Wu, Hao [1 ]
He, Wenze [2 ]
Li, Xiongfei [2 ]
Liang, Yanchun [1 ]
机构
[1] Minist Educat, Zhuhai Coll Sci & Technol, Zhuhai Sub Lab, Key Lab Symbol Computat & Knowledge Engn, Zhuhai 519041, Peoples R China
[2] Jilin Univ, Coll Comp Sci & Tech, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130023, Peoples R China
来源
2023 15TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE, ICACI | 2023年
关键词
ethnic pattern; generative adversarial network; image generation; super-resolution reconstruction;
D O I
10.1109/ICACI58115.2023.10146174
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we take Mongolian ethnic patterns as the research object and conduct a technical study on ethnic pattern generation and super-resolution reconstruction based on deep learning generative adversarial networks to address the problems of low quality of ethnic pattern data collection and lack of innovation. In this paper, we use a database including 1621 Mongolian ethnic patterns, train StyleGAN2 on the pre-processed images, and generate images After that, we use ESRGAN to perform super-resolution reconstruction on the generated images to generate high-resolution patterns with Mongolian style. The model designed in this paper can generate high quality images with ethnic characteristics in the case of insufficient original data. Compared with the time-consuming and labor-intensive traditional ethnic pattern design methods, the model designed in this paper lowers the threshold of ethnic pattern innovation and contributes to the innovative design of ethnic patterns to a certain extent, which has some positive significance for the protection and inheritance of ethnic patterns.
引用
收藏
页数:6
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