Human Image Generation

Human image generation focuses on creating realistic and controllable images of people using artificial intelligence, primarily aiming to improve image quality, pose accuracy, and address biases. Current research heavily utilizes diffusion models, often incorporating additional control mechanisms like pose priors, text prompts, and reference images to guide the generation process, with advancements in techniques like graph-based relations and multi-view fusion improving results. This field is significant for its applications in e-commerce, virtual reality, and artistic creation, while also raising important ethical considerations regarding bias mitigation and fairness in AI-generated imagery.