Ein innovatives Framework für die Bildsuperauflösung, das auf Cross-modal Priors basiert.
Diffusion-based methods in Image Super-Resolution benefit from cross-modal priors to generate high-fidelity and realistic images.
The author proposes the XPSR framework to address challenges in restoring semantic details in Image Super-Resolution by leveraging cross-modal priors from Multimodal Large Language Models (MLLMs) and introducing Semantic-Fusion Attention and Degradation-Free Constraint.