Shadow puppetry is a traditional Chinese folk art with significant cultural heritage value. However, due to the influence of modern new media, this cultural treasure is gradually disappearing from public view. To address this issue, we have developed "ShadowStudio," a comprehensive digital shadow puppetry creation and sharing system that integrates creation, sharing, and educational functions. This system, built on the Unity 3D engine, allows users to freely create shadow puppetry performances and upload them online for others to download and play. Additionally, users can access an embedded database of shadow puppetry artifacts to learn about the cultural heritage of shadow puppetry. We also conducted field activities to collect feedback from thirty participants. The results indicate that our system significantly enhances users' interest in concepts related to shadow puppetry.
KEYWORDS: Diffusion, Education and training, Data modeling, Machine learning, Systems modeling, Lithium, Visual process modeling, Image processing, Statistical modeling, Aliasing
The exploration of stable diffusion model for generating traditional Chinese painting-style line drawings is a promising field. However, the results directly generated by fine-tuning the stable diffusion model using the line drawing dataset have flaws in details, especially on the face. These flaws include unclear faces, facial feature aliasing, and inability to show expression. Therefore, we propose a method of line drawing generation and face optimization based on stable diffusion and matting technology. The dataset we used for fine-tuning is divided into two parts: the whole character line drawing and the face part of the line drawing, The face mask is obtained by matting after generating line drawing using a fine-tuned stable diffusion model. Finally, the face part of the figure is redrawn in the mask area by inpainting to achieve the face optimization effect. Through the above steps, we can not only generate line drawing but also solve the problems of unclear faces, facial feature aliasing, and inability to show expression.
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