Diffusion-based image super-resolution (SR) methods have achieved remarkable success
by leveraging large pre-trained text-to-image diffusion models as priors. However, these …

Cardiac magnetic resonance imaging (CMRI) can help experts quickly diagnose
cardiovascular diseases. Due to the patient's breathing and slight movement during the …

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 …

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 …

Deep generative models have garnered significant attention in low-level vision tasks due to
their generative capabilities. Among them, diffusion model-based solutions, characterized by …

Diffusion models significantly improve the quality of super-resolved images with their
impressive content generation capabilities. However, the huge computational costs limit the …

Blind all-in-one image restoration models aim to recover a high-quality image from an input
degraded with unknown distortions. However, these models require all the possible …

Blind face restoration (BFR) is fundamentally challenged by the extensive range of
degradation types and degrees that impact model generalization. Recent advancements in …

We propose Lodge++, a choreography framework to generate high-quality, ultra-long, and
vivid dances given the music and desired genre. To handle the challenges in computational …

The human whole-body X-rays could offer a valuable reference for various applications,
including medical diagnostics, digital animation modeling, and ergonomic design. The …