In recent years, the image and video coding technologies have advanced by leaps and
bounds. However, due to the popularization of image and video acquisition devices, the …

Deep learning architectures are now pervasive and filled almost all applications under
image processing, computer vision, and biometrics. The attractive property of feature …

This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …

Image restoration is a long-standing low-level vision problem that aims to restore high-
quality images from low-quality images (eg, downscaled, noisy and compressed images) …

Deep neural networks (DNN) have achieved great success in image restoration. However,
most DNN methods are designed as a black box, lacking transparency and interpretability …

Images captured under low-light conditions often suffer from (partially) poor visibility.
Besides unsatisfactory lightings, multiple types of degradation, such as noise and color …

Diffusion model (DM) has achieved SOTA performance by modeling the image synthesis
process into a sequential application of a denoising network. However, different from image …

Blind face restoration usually relies on facial priors, such as facial geometry prior or
reference prior, to restore realistic and faithful details. However, very low-quality inputs …

Recent works on plug-and-play image restoration have shown that a denoiser can implicitly
serve as the image prior for model-based methods to solve many inverse problems. Such a …

Images captured under low-light conditions often suffer from (partially) poor visibility.
Besides unsatisfactory lightings, multiple types of degradations, such as noise and color …