Super Resolution Diffusion Model

Super-resolution diffusion models are advancing image and video generation by enhancing low-resolution inputs to achieve significantly higher resolutions. Current research focuses on cascading multiple diffusion models to progressively refine outputs, often incorporating transformer architectures and employing techniques like implicit neural representations to handle large-scale scenes efficiently. These advancements are impacting diverse fields, enabling realistic terrain generation, high-quality video synthesis, and improved text-to-image models with enhanced detail and control, ultimately pushing the boundaries of digital content creation.