A High-Precision Character Cartoon Style Transfer Method Based on VToonify and Diffusion Models

Abstract

In recent years, the technology for converting character images into cartoons has gained widespread attention on short video platforms, with diffusion models particularly standing out in the field of image style transfer. However, existing methods still have shortcomings in detail handling and character feature control. To address these issues, this paper proposes a high-precision character style transfer framework that combines the VToonify model with diffusion models. By using Mask-based integration of VToonify and Diffusion models, we significantly enhance character detail representation while maintaining overall style consistency. Experimental results demonstrate that this model outperforms existing similar generative models in both detail control and overall effectiveness, offering a new solution for high-quality personalized style transfer.