Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

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 …

Understanding shadows from a single image consists of two types of task in previous
studies, containing shadow detection and shadow removal. In this paper, we present a multi …

Shadow detection is a fundamental and challenging task, since it requires an understanding
of global image semantics and there are various backgrounds around shadows. This paper …

Shadow removal is an essential task for scene understanding. Many studies consider only
matching the image contents, which often causes two types of ghosts: color in-consistencies …

Shadow detection is an important and challenging task for scene understanding. Despite
promising results from recent deep learning based methods. Existing works still struggle with …

We introduce scGAN, a novel extension of conditional Generative Adversarial Networks
(GAN) tailored for the challenging problem of shadow detection in images. Previous …

We present a framework to automatically detect and remove shadows in real world scenes
from a single image. Previous works on shadow detection put a lot of effort in designing …

In this paper, we address the problem of shadow detection and removal from single images
of natural scenes. Differently from traditional methods that explore pixel or edge information …

Existing shadow detection datasets often contain missing or mislabeled shadows, which can
hinder the performance of deep learning models trained directly on such data. To address …