Collaborative Diffusion enables face generation and editing using multiple modalities (e.g., text, sketch, sparse facial landmarks) as control signals. The approach uses pre-trained uni-modal diffusion models in a collaborative manner during the reverse diffusion process. The method supports both synthesizing new images from multi-modal inputs and editing real images while preserving identity characteristics.