Diffusion models (DMs) have disrupted the image super-resolution (SR) field and further
closed the gap between image quality and human perceptual preferences. They are easy to …

Real-world image super-resolution (Real-ISR) aims to reconstruct high-resolution images
from low-resolution inputs degraded by complex, unknown processes. While many Stable …

This study presents a new image super-resolution (SR) technique based on diffusion
inversion, aiming at harnessing the rich image priors encapsulated in large pre-trained …

Facial super-resolution (FSR) is a critical research area whose goal is to improve visual
quality by converting low-resolution facial images to high resolution ones. Research in FSR …

Diffusion models are proficient at generating high-quality images. They are however
effective only when operating at the resolution used during training. Inference at a scaled …

There has been immense progress recently in the visual quality of Stable Diffusion-based
Super Resolution (SD-SR). However, deploying large diffusion models on computationally …

In recent years, there has been significant interest in Super-Resolution (SR), which focuses
on generating a high-resolution image from a low-resolution input. Deep learningbased …