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 …

This tutorial presents a hands-on view of the field of multi-view stereo with a focus on
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …

Being data-driven is one of the most iconic properties of deep learning algorithms. The birth
of ImageNet drives a remarkable trend of" learning from large-scale data" in computer vision …

Once an academic venture, autonomous driving has received unparalleled corporate
funding in the last decade. Still, operating conditions of current autonomous cars are mostly …

Abstract We present Multi-Baseline Radiance Fields (MuRF) a general feed-forward
approach to solving sparse view synthesis under multiple different baseline settings (small …

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 …

This work presents a Multi-View Stereo system for robust and efficient dense modeling from
unstructured image collections. Our core contributions are the joint estimation of depth and …

Multiview stereo aims to reconstruct scene depth from images acquired by a camera under
arbitrary motion. Recent methods address this problem through deep learning, which can …

We propose a fundamentally novel approach to real-time visual odometry for a monocular
camera. It allows to benefit from the simplicity and accuracy of dense tracking which does …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …