Figure 2. An overview of the FaithDiff, which takes LQ images and image descriptions as inputs and restores HQ images via diffusion
process. To fully leverage the power of LDMs, we propose to unleash diffusion priors. An alignment module is developed to effectively
incorporate the features extracted from LQ images with the noisy latent of the diffusion model. We jointly optimize the encoder, the
alignment module, and the diffusion model, which can benefit from their interplay and lead to faithful SR images with high visual quality.