Enhancing Human Image Generation with Human-Centric Priors in Diffusion Models

The author proposes integrating human-centric priors directly into the model fine-tuning stage to improve human image generation without extra conditions at inference. By introducing a Human-centric Alignment loss and scale-aware constraints, the method enhances structural accuracy and detail richness in generated images.