翻译(生物学)
图像(数学)
人工智能
频域
计算机科学
领域(数学分析)
模式识别(心理学)
计算机视觉
数学
生物
数学分析
生物化学
信使核糖核酸
基因
作者
Zijian Zhu,Yaochen Li,Yifan Li,Jianlong Yang,Peijun Chen,Yuehu Liu
出处
期刊:Proceedings of the ... AAAI Conference on Artificial Intelligence
[Association for the Advancement of Artificial Intelligence (AAAI)]
日期:2024-03-24
卷期号:38 (7): 7820-7827
标识
DOI:10.1609/aaai.v38i7.28617
摘要
For the task of unsupervised image translation, transforming the image style while preserving its original structure remains challenging. In this paper, we propose an unsupervised image translation method with structural enhancement in frequency domain named SEIT. Specifically, a frequency dynamic adaptive (FDA) module is designed for image style transformation that can well transfer the image style while maintaining its overall structure by decoupling the image content and style in frequency domain. Moreover, a wavelet-based structure enhancement (WSE) module is proposed to improve the intermediate translation results by matching the high-frequency information, thus enriching the structural details. Furthermore, a multi-scale network architecture is designed to extract the domain-specific information using image-independent encoders for both the source and target domains. The extensive experimental results well demonstrate the effectiveness of the proposed method.
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