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

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 …

Stereo matching is a fundamental building block for many vision and robotics applications.
An informative and concise cost volume representation is vital for stereo matching of high …

The deep multi-view stereo (MVS) and stereo matching approaches generally construct 3D
cost volumes to regularize and regress the output depth or disparity. These methods are …

Temporal action proposal generation is an challenging and promising task which aims to
locate temporal regions in real-world videos where action or event may occur. Current …

Stereo matching estimates the disparity between a rectified image pair, which is of great
importance to depth sensing, autonomous driving, and other related tasks. Previous works …

Dot-product attention has wide applications in computer vision and natural language
processing. However, its memory and computational costs grow quadratically with the input …

In this paper, we propose an accurate edge detector using richer convolutional features
(RCF). Since objects in natural images possess various scales and aspect ratios, learning …

Our goal is to significantly speed up the runtime of current state-of-the-art stereo algorithms
to enable real-time inference. Towards this goal, we developed a differentiable PatchMatch …

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 …