Stage Diffusion

Stage diffusion models are a class of generative models that iteratively refine an image or signal through multiple stages, leveraging the strengths of diffusion processes for high-fidelity generation. Current research focuses on improving the controllability and efficiency of these models, often employing hierarchical architectures or incorporating additional conditioning information (e.g., landmarks, text descriptions) to guide the generation process at each stage. This approach is proving valuable in diverse applications, including high-resolution image editing, realistic talking head generation, and even human silhouette segmentation from radio frequency signals, demonstrating the versatility and power of staged diffusion for complex data synthesis and manipulation.