Stable Diffusion Model

Stable Diffusion models are a class of generative AI models primarily used for high-quality image synthesis from text prompts or other image inputs. Current research focuses on improving efficiency (through model compression and faster sampling techniques), enhancing control and fidelity (via fine-tuning methods and prompt engineering), and mitigating risks associated with data privacy and copyright infringement (through watermarking and data attribution techniques). These models are significantly impacting various fields, including scientific visualization, medical imaging, and creative design, by enabling efficient data augmentation and the generation of novel, realistic images for diverse applications.