Diffusion Models

Diffusion models work by gradually adding noise to training images and then learning to reverse this process. They start with random noise and iteratively refine it into clear images guided by the learned patterns from training data. This approach has proven particularly effective for high-quality image generation and editing.

Image generation from text image editing and inpainting medical image synthesis architectural visualization