Customizing Guidance Degrees for Semantic Units in Text-to-Image Diffusion Models

Classifier-Free Guidance (CFG) in text-to-image diffusion models suffers from spatial inconsistency in semantic strengths and suboptimal image quality. To address this, we propose Semantic-aware CFG (S-CFG) to customize the guidance degrees for different semantic units.