State-of-the-art automated image orientation (Structure from Motion) and dense image
matching (Multiple View Stereo) methods commonly used to produce 3D information from …

With the evolution of 5G and Internet of Things technologies, Mobile Edge Computing (MEC)
has emerged as a major computing paradigm. Compared to cloud computing, MEC …

Camera pose estimation is a long-standing computer vision problem that to date often relies
on classical methods, such as handcrafted keypoint matching, RANSAC and bundle …

We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for
high-resolution multi-view stereo. With high computation speed and low memory …

Humans can orient themselves in their 3D environments using simple 2D maps. Differently,
algorithms for visual localization mostly rely on complex 3D point clouds that are expensive …

We present IterMVS, a new data-driven method for high-resolution multi-view stereo. We
propose a novel GRU-based estimator that encodes pixel-wise probability distributions of …

Abstract 360deg cameras can capture complete environments in a single shot, which makes
360deg imagery alluring in many computer vision tasks. However, monocular depth …

Robust and accurate visual-inertial estimation is crucial to many of today's challenges in
robotics. Being able to localize against a prior map and obtain accurate and drift-free pose …

In this paper, we propose a practical three-dimensional (3D) real-scene reconstruction
framework named Deep3D, which is paired with a deep learning based multi-view stereo …

This paper presents a convolutional neural network based approach for estimating the
relative pose between two cameras. The proposed network takes RGB images from both …