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基于自注意机制的乳源瑶绣自动生成与应用研究

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针对当前风格迁移模型在处理乳源瑶绣图像时存在的局限性,尤其是难以有效处理抽象几何形变和生成图像中噪点较多的问题,提出了一种 SA-CycleGAN的乳源瑶绣风格迁移模型.通过融入自注意力机制,同时将生成对抗损失的目标函数替换为 WGAN,显著增强模型对乳源瑶绣风格特征的捕捉能力,从而优化了风格映射的质量.在应用中,该模型不仅为乳源瑶绣图案的自动生成和在线设计系统提供了坚实的技术支撑,也推动了相应数据库和数字共享平台的构建.通过严谨的对比实验,验证了优化后的 SA-CycleGAN模型生成的乳源瑶绣纹样因子在评价指标上表现优异,其FID值相较原始CycleGAN模型降低了 16.1%,而IS值相对提高了 13.2%,图像质量得到显著提升,且视觉上更为贴近原始的乳源瑶绣风格.乳源瑶绣图案设计系统的建立大幅提升了设计效率,为民族纹样的传承与创新注入了新的活力与价值.
Research on automatic generation and application of Ruyuan Yao embroidery based on self-attention mechanism
To address the limitations of current style migration models in processing Ruyuan Yao embroidery images,especially in effectively handling abstract geometric transformations and the high noise in the generated images,a style migration model for Ruyuan Yao embroidery named SA-CycleGAN was proposed.By incorporating a self-attention mechanism and replacing the objective function for generating the adversarial loss with WGAN,the model significantly enhanced its ability to capture the style features of Ruyuan Yao embroidery,thereby optimizing the quality of style mapping.In terms of application,the proposed SA-CycleGAN model not only provided solid technical support for the automatic generation and online design system of Ruyuan Yao embroidery patterns,but also facilitated the construction of the corresponding database and digital sharing platform.Rigorous comparative experiments demonstrated that the optimized SA-CycleGAN model achieved excellent performance in the evaluation indexes for Ruyuan Yao embroidery pattern factors,its FID value was reduced by 16.1%,and the IS value was relatively improved by 13.2%compared with the original CycleGAN model,resulting in significantly improved image quality that was visually closer to the original Ruyuan Yao embroidery style.The establishment of the pattern design system of Ruyuan Yao embroidery greatly enhanced the design efficiency,injecting new vigor and value into the preservation and innovation of the ethnic group patterns.

self-attention mechanismstyle transferRuyuan Yao embroiderypatterngenerative adversarial networkinteraction design

刘宗明、洪唯、龙睿、祝越、张小宇

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陕西科技大学设计与艺术学院,陕西 西安 710016

软通智慧科技有限公司,广东 深圳 518000

自注意力机制 风格迁移 乳源瑶绣 纹样 生成对抗网络 交互设计

国家社会科学基金艺术学项目

23BG131

2024

图学学报
中国图学学会

图学学报

CSTPCD北大核心
影响因子:0.73
ISSN:2095-302X
年,卷(期):2024.45(5)