Face Stylization

Face stylization aims to transform facial images into various artistic styles, preserving key facial features while applying desired aesthetic changes. Recent research focuses on developing efficient one-shot and training-free methods, often leveraging generative adversarial networks (GANs), diffusion models, and vision transformers to achieve high-quality stylization with minimal training data or even without any training. These advancements are significant for applications in digital art, entertainment, and potentially personalized image editing, offering faster and more flexible style transfer capabilities.