Implicit Diffusion Models for Continuous Super-Resolution

Understand

Image super-resolution (SR) has attracted increasing attention due to its wide applications.

• However, current SR methods generally suffer from over-smoothing and artifacts, and most work only with fixed magnifications.
• This paper introduces an Implicit Diffusion Model (IDM) for high-fidelity continuous image super-resolution.
• IDM integrates an implicit neural representation and a denoising diffusion model in a unified end-to-end framework, where the implicit neural representation is adopted in the decoding process to learn continuous-resolution representation.