华东师范大学学报（自然科学版）Issue(2)：119-130,12.DOI:10.3969/j.issn.1000-5641.2024.02.013
基于隐层傅里叶卷积的非平稳纹理合成方法
Hidden layer Fourier convolution for non-stationary texture synthesis
何鑫鑫 1宋海川1
作者信息
- 1. 华东师范大学计算机科学与技术学院,上海 200062
- 折叠
摘要
Abstract
The remarkable achievements of deep learning in computer vision have led to significant development in example-based texture synthesis.The texture synthesis model using neural networks mainly includes local components,such as convolution and up/down sampling,which is unsuitable for capturing irregular structural attributes in non-stationary textures.Inspired by the frequency and space domain duality,a non-stationary texture synthesis method based on hidden layer Fourier convolution is proposed in this study.The proposed method uses the generative adversarial network as the basic architecture,performs feature splitting along the channel in the hidden layer,and builds a local branch in the image domain and a global branch in the frequency domain to consider visual perception and structural information.Experimental results show that this method can handle structurally challenging non-stationary texture exemplars.Compared with state-of-the-art methods,the method yielded better results in the learning and expansion of large-scale structures.关键词
纹理合成/非平稳纹理/傅里叶卷积/生成对抗网络Key words
texture synthesis/non-stationary texture/Fourier convolution/generative adversarial network分类
信息技术与安全科学引用本文复制引用
何鑫鑫,宋海川..基于隐层傅里叶卷积的非平稳纹理合成方法[J].华东师范大学学报（自然科学版）,2024,(2):119-130,12.
