Abstract
To address the problem of missing details in the general dress pattern line extraction method, we propose a traditional dress pattern line extraction method based on the improved CycleGAN. First, we input the traditional dress pattern image and extract the outline edge image by using a bi-directional cascade network. Afterwards, we construct an improved CycleGAN network model, input the traditional dress pattern image and its outline edge image into the generator model for line drawing extraction, use the discriminator model to discriminate between the generated image and the real image, and output the binary classification matrix. Finally, we construct the adversarial loss, cycle consistency loss and contour consistency loss functions to constrain the network model, output a detail rich line drawing image. Experiments show that the proposed method achieves the extraction of traditional dress pattern line images with perfect details, and the generated traditional dress pattern line images have more realistic and natural lines compared with other dress pattern line extraction methods. The method can accurately extract traditional costume pattern line images and contribute to the preservation and transmission of Chinese traditional costume culture.
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This work was supported by the Funding Project of Beijing Social Science Foundation (No. 20YTB011).
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Cai, X., Jia, S., Yao, J., Wu, Y., Sun, H. (2024). An Image Extraction Method for Traditional Dress Pattern Line Drawings Based on Improved CycleGAN. In: Sheng, B., Bi, L., Kim, J., Magnenat-Thalmann, N., Thalmann, D. (eds) Advances in Computer Graphics. CGI 2023. Lecture Notes in Computer Science, vol 14496. Springer, Cham. https://doi.org/10.1007/978-3-031-50072-5_25
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DOI: https://doi.org/10.1007/978-3-031-50072-5_25
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