Controllable Generation with Text-to-Image Diffusion Models: A Survey

Understand

In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guided generative functions.

• However, relying solely on text for conditioning these models does not fully cater to the varied and complex requirements of different applications and scenarios.
• Acknowledging this shortfall, a variety of studies aim to control pre-trained text-to-image (T2I) models to support novel conditions.
• In this survey, we undertake a thorough review of the literature on controllable generation with T2I diffusion models, covering both the theoretical foundations and practical advancements in this domain.