With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …

Structured illumination microscopy (SIM) has become the standard for next-generation wide-
field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view …

Large-scale labeled data are generally required to train deep neural networks in order to
obtain better performance in visual feature learning from images or videos for computer …

This paper presents HITNet, a novel neural network architecture for real-time stereo
matching. Contrary to many recent neural network approaches that operate on a full …

Estimating depth from RGB images is a long-standing ill-posed problem, which has been
explored for decades by the computer vision, graphics, and machine learning communities …

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 …

A key component of Simultaneous Localization and Map** (SLAM) systems is the joint
optimization of the estimated 3D map and camera trajectory. Bundle adjustment (BA) is the …

We study the problem of shape generation in 3D mesh representation from a few color
images with known camera poses. While many previous works learn to hallucinate the …

Deep convolutional neural networks trained end-to-end are the state-of-the-art methods to
regress dense disparity maps from stereo pairs. These models, however, suffer from a …

Motivated by augmented and virtual reality applications such as telepresence, there has
been a recent focus in real-time performance capture of humans under motion. However …