Abstract

Abstract This paper firstly analyzes the specific application of velvet flowers on women’s dresses from the perspective of fashion aesthetics and with the understanding of the background and development trend of dresses. Secondly, based on 3D visual perception, we propose the optimization of the normalization method and loss function optimization, which can improve the migration speed and generation quality of velvet flower design, and then seamlessly fit it to the dress base map by Poisson fusion to realize the intelligent design of velvet flower in dresses driven by 3D visual perception. Then, the color features and attributes of the floral in the dress are studied, and the HSV color space model is used to extract the high-frequency colors and attributes of the dress. Then, the floral design is digitized, and the dress design is driven by 3D visual perception is studied and analyzed. The results show that the loss value of the dress design style migration network trained based on AdaN is the smallest, and the loss value is reduced by 0.19 compared to the dress design style migration network using IN and 0.31 compared to BN. The velvet flower design on the dress design base map can be implemented based on the foundation provided by this study.

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