Predicting depth is an essential component in understanding the 3D geometry of a scene.
While for stereo images local correspondence suffices for estimation, finding depth relations …

The computer-based approach is required for the non-invasive detection of chronic liver
diseases that are asymptomatic, progressive, and potentially fatal in nature. In this study, we …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

Deep learning has been revolutionizing information processing in many fields of science
and engineering owing to the massively growing amounts of data and the advances in deep …

A light-field camera captures both the intensity and the direction of incoming light,,,–. This
enables a user to refocus pictures and afterwards reconstruct information on the depth of …

Many fundamental image-related problems involve deconvolution operators. Real blur
degradation seldom complies with an deal linear convolution model due to camera noise …

In this paper we present a new method for estimating the optical transmission in hazy
scenes given a single input image. Based on this estimation, the scattered light is eliminated …

Convolutional neural networks (CNNs) excel in a wide variety of computer vision
applications, but their high performance also comes at a high computational cost. Despite …

We present a new image editing method, particularly effective for sharpening major edges
by increasing the steepness of transition while eliminating a manageable degree of low …

The heavy-tailed distribution of gradients in natural scenes have proven effective priors for a
range of problems such as denoising, deblurring and super-resolution. However, the use of …