Resolution Diffusion

Resolution diffusion research focuses on improving the resolution and efficiency of diffusion models, primarily for image and 3D model generation. Current efforts concentrate on developing techniques like patch-wise extrapolation and multi-resolution frameworks to enhance both the speed and quality of high-resolution generation, often leveraging existing pre-trained models. These advancements are significant for various applications, including privacy-preserving recommender systems and high-fidelity text-to-3D content creation, by enabling the generation of more realistic and detailed synthetic data or models. The development of efficient infinite-resolution models also represents a key area of exploration.