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 …

The intrinsic image decomposition aims to retrieve “intrinsic” properties of an image, such as
shading and reflectance. To make it possible to quantitatively compare different approaches …

We present an algorithm that uses multiple cues to recover shading and reflectance intrinsic
images from a single image. Using both color information and a classifier trained to …

We present a model for intrinsic decomposition of RGB-D images. Our approach analyzes a
single RGB-D image and estimates albedo and shading fields that explain the input. To …

Intrinsic image decomposition is the process of recovering the image formation components
(reflectance and shading) from an image. Previous methods employ either explicit priors to …

Detecting shadows from images can significantly improve the performance of several vision
tasks such as object detection and tracking. Recent approaches have mainly used …

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

In this paper we propose a novel method for detecting and removing shadows from a single
image thereby obtaining a high‐quality shadow‐free image. With minimal user assistance …

We propose a method for intrinsic image decomposition based on retinex theory and texture
analysis. While most previous methods approach this problem by analyzing local gradient …

In this paper, we propose a simple but effective shadow removal method using a single input
image. We first derive a 2-D intrinsic image from a single RGB camera image based solely …