Portrait Generation

Portrait generation research focuses on creating realistic and controllable synthetic portraits, often from limited input like a single image or text description. Current efforts leverage generative adversarial networks (GANs), diffusion models, and neural radiance fields (NeRFs), often incorporating 3D modeling for improved realism and view consistency, along with multimodal prompts (text, images) for enhanced control. This field is significant for applications in video editing, virtual reality, and personalized content creation, driving advancements in image synthesis and 3D modeling techniques.