We propose residual denoising diffusion models (RDDM) a novel dual diffusion process that
decouples the traditional single denoising diffusion process into residual diffusion and noise …

Shadow removal aims at restoring the image content within shadow regions, pursuing a
uniform distribution of illumination that is consistent between shadow and non-shadow …

Single-image shadow removal is a significant task that is still unresolved. Most existing deep
learning-based approaches attempt to remove the shadow directly, which cannot deal with …

Shadow removal from remote sensing images is still an open issue. Recently, deep network
training on unpaired data is preferable since corresponding ground truths of shadow images …

In recent years, deep learning has emerged as an important tool for image shadow removal.
However, existing methods often prioritize shadow detection and, in doing so, they …

Removing soft and self shadows that lack clear boundaries from a single image is still
challenging. Self shadows are shadows that are cast on the object itself. Most existing …

Portrait shadow removal is a challenging task due to the complex surface of the face.
Although existing work in this field makes substantial progress, these methods tend to …

In this paper, we introduce a two-stage deep learning-based image restoration network and
its application to remove shadow information from a single image, named by ESCNet …

Remote sensing shadow removal is an open issue. Previous studies focus on working in the
spatial dimension, ignoring the potential of the Fourier dimension, while illumination …

Shadows can originate from occlusions in both direct and indirect illumination. Although
most current shadow removal research focuses on shadows caused by direct illumination …