Ensuring Face Consistency and Image Naturalness in Multi-Person Image Generation with Diffusion ModelsŽakelj, Mark (Avtor) Marolt, Matija (Mentor) Diffusion modelsImage generationFacial consistencyDiffusion models have been widely used for consistent subject generation, but current methods are mostly focused on consistency of a single subject in an image, while consistent multi-subject generation remains an unexplored problem. We propose a method that combines diffusion models with IP-Adapters for facial consistency, ControlNet for ensuring image variability, and facial inpainting for improved facial quality and consistency. We introduce our own module for facial matching, which improves prompt adherence in cases where the age of the subjects varies significantly or their gender is different. Our method produces images of great quality with facial consistency limited only by the underlying IP-Adapter methods.20242024-11-29 10:40:01Magistrsko delo/naloga165288sl