Recent advancements in computer vision have enabled wide-ranging applications in every
field of life. One such application area is fresh produce classification, but the classification of …

The field of surveillance and forensics research is currently shifting focus and is now
showing an ever increasing interest in the task of people reidentification. This is the task of …

Low-light images typically suffer from two problems. First, they have low visibility (ie, small
pixel values). Second, noise becomes significant and disrupts the image content, due to low …

Recent years have witnessed the increasing popularity of learning based methods to
enhance the color and tone of photos. However, many existing photo enhancement methods …

Abstract Machine learning techniques work best when the data used for training resembles
the data used for evaluation. This holds true for learned single-image denoising algorithms …

Rain streaks, particularly in heavy rain, not only degrade visibility but also make many
computer vision algorithms fail to function properly. In this paper, we address this visibility …

Robust recovery of lost colors in underwater images remains a challenging problem. We
recently showed that this was partly due to the prevalent use of an atmospheric image …

Improvements in color constancy have arisen from the use of convolutional neural networks
(CNNs). However, the patch-based CNNs that exist for this problem are faced with the issue …

We introduce a deep learning approach to realistically edit an sRGB image's white balance.
Cameras capture sensor images that are rendered by their integrated signal processor (ISP) …

For decades, photographs have been used to document space-time events and they have
often served as evidence in courts. Although photographers are able to create composites of …