The emerging capability to 3D print a diverse palette of functional inks will enable the mass
democratization of patient-specific wearable devices and smart biomedical implants for …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

We propose a novel deep learning architecture for regressing disparity from a rectified pair
of stereo images. We leverage knowledge of the problem's geometry to form a cost volume …

We present a challenging new dataset for autonomous driving: the Oxford RobotCar
Dataset. Over the period of May 2014 to December 2015 we traversed a route through …

Motivated by the limitations of existing multi-view stereo benchmarks, we present a novel
dataset for this task. Towards this goal, we recorded a variety of indoor and outdoor scenes …

Disparity estimation for binocular stereo images finds a wide range of applications.
Traditional algorithms may fail on featureless regions, which could be handled by high-level …

This paper presents StereoNet, the first end-to-end deep architecture for real-time stereo
matching that runs at 60 fps on an NVidia Titan X, producing high-quality, edge-preserved …

We present a comprehensive overview of the stereoscopic Intel RealSense RGBD imaging
systems. We discuss these systems' mode-of-operation, functional behavior and include …

We present a method for extracting depth information from a rectified image pair. Our
approach focuses on the first stage of many stereo algorithms: the matching cost …

This paper provides a review for absolute phase recovery methods that are applicable for
digital fringe projection (DFP) systems. Specifically, we present two conventional absolute …