This paper presents a literature survey on existing disparity map algorithms. It focuses on
four main stages of processing as proposed by Scharstein and Szeliski in a taxonomy and …

A significant amount of research in the field of stereo vision has been published in the past
decade. Considerable progress has been made in improving accuracy of results as well as …

Quantum error correction is an indispensable ingredient for scalable quantum computing. In
this Perspective we discuss a particular class of quantum codes called “quantum low-density …

In this paper we propose a novel approach to binocular stereo for fast matching of high-
resolution images. Our approach builds a prior on the disparities by forming a triangulation …

Inferring the depth of transparent or mirror (ToM) surfaces represents a hard challenge for
either sensors, algorithms, or deep networks. We propose a simple pipeline for learning to …

In this paper, we consider the problem of stereo matching using loopy belief propagation.
Unlike previous methods which focus on the original spatial resolution, we hierarchically …

This paper proposes a novel framework integrating the principles of active stereo in
standard passive camera systems without a physical pattern projector. We virtually project a …

Time-of-flight range sensors have error characteristics, which are complementary to passive
stereo. They provide real-time depth estimates in conditions where passive stereo does not …

Markov random fields are widely used to model many computer vision problems that can be
cast in an energy minimization framework composed of unary and pairwise potentials. While …

Event stereo matching is an emerging technique to estimate depth from neuromorphic
cameras; however, events are unlikely to trigger in the absence of motion or the presence of …