AI Face Swapping Image Synthesis Framework FaceStudio Supports Multi-Person Image Synthesis
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FaceStudio is an identity-preserving synthesis method designed to maintain subject identity during image generation while adding personalized styles. Compared to traditional methods, FaceStudio achieves fast and efficient image generation through a direct feed-forward mechanism, avoiding tedious tuning and the need for multiple reference images.
Project address: https://icoz69.github.io/facestudio/
Through a hybrid guidance framework that combines artistic images, facial images, and text prompts, the model enables the generation of various applications, such as artistic portraits and identity-blended images. Experimental results show that FaceStudio outperforms existing benchmark models and prior research in terms of efficiency and high-fidelity preservation of subject identity.
The model supports multi-person image synthesis. It enables mixed-style image generation and identity blending. Compared to baseline methods, our approach demonstrates significant advantages in facial similarity and generation time by using text and images as guidance.