This work reviews the results of the NTIRE 2024 Challenge on Shadow Removal. Building
on the last year edition the current challenge was organized in two tracks with a track …

Image restoration (IR) has been an indispensable and challenging task in the low-level
vision field, which strives to improve the subjective quality of images distorted by various …

The emergence of large models, also known as foundation models, has brought significant
advancements to AI research. One such model is Segment Anything (SAM), which is …

We consider the generic problem of detecting low-level structures in images, which includes
segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow …

The emergence of large models, also known as foundation models, has brought significant
advancements to AI research. One such model is Segment Anything (SAM), which is …

Existing state-of-the-art salient object detection networks rely on aggregating multi-level
features of pre-trained convolutional neural networks (CNNs). However, compared to high …

Recent deep learning methods have achieved promising results in image shadow removal.
However, their restored images still suffer from unsatisfactory boundary artifacts, due to the …

We present a general learning-based solution for restoring images suffering from spatially-
varying degradations. Prior approaches are typically degradation-specific and employ the …

We propose a new end-to-end single image dehazing method, called Densely Connected
Pyramid Dehazing Network (DCPDN), which can jointly learn the transmission map …

Severe weather conditions, such as rain and snow, adversely affect the visual quality of
images captured under such conditions, thus rendering them useless for further usage and …