#StyleAvatar3D

This article explores a cutting-edge method for creating high-fidelity 3D avatars by integrating image-text diffusion models with a GAN framework. Using pre-trained models, it generates stylized, multi-view avatars, tackling pose-image alignment with innovative view-specific prompts and a refined GAN discriminator. It also enhances diversity through attribute-based prompts and includes a style diffusion model for avatar creation from image inputs, offering superior visual quality and diversity compared to existing methods.