This paper introduces training of shadow detectors under the large-scale dataset paradigm.
This was previously impossible due to the high cost of precise shadow annotation. Instead …

The objective of this work is to detect shadows in images. We pose this as the problem of
labeling image regions, where each region corresponds to a group of superpixels. To …

In this paper, we present a novel shadow detection framework by investigating the mutual
complementary mechanisms contained in this specific task. Our method is based on a key …

We present a novel learning-based framework for shadow detection from a single image.
The local structure of shadow boundaries as well as the global interactions of the shadow …

In recent years, various shadow detection methods from a single image have been
proposed and used in vision systems; however, most of them are not appropriate for the …

A user-centric method for fast, interactive, robust, and high-quality shadow removal is
presented. Our algorithm can perform detection and removal in a range of difficult cases …

The objective of this work is to detect shadows in images. We pose this as the problem of
labeling image regions, where each region corresponds to a group of superpixels. To …

Today's mainstream shadow detection methods are manually designed via a case-by-case
approach. Accordingly, these methods may only be able to detect shadows for specific …

Recent shadow detection algorithms have shown initial success on small datasets of images
from specific domains. However, shadow detection on broader image domains is still …

Recent shadow detection algorithms have shown initial success on small datasets of images
from specific domains. However, shadow detection on broader image domains is still …