What is conditional image generation in diffusion models?

Conditional diffusion models generate images guided by text, class labels, or other inputs.

Diffusion models learn to reverse a noise-adding process step by step. Conditional diffusion adds guidance signals such as text embeddings or class labels into the denoising process. This allows controllable generation, where outputs align with given conditions while maintaining high visual fidelity.