Visual localization is the task of accurate camera pose estimation in a known scene. It is a
key problem in computer vision and robotics, with applications including self-driving cars …

Visual Localization is one of the key enabling technologies for autonomous driving and
augmented reality. High quality datasets with accurate 6 Degree-of-Freedom (DoF) …

Visual localization, ie, camera pose estimation in a known scene, is a core component of
technologies such as autonomous driving and augmented reality. State-of-the-art …

Visual localization tackles the challenge of estimating the camera pose from images by
using correspondence analysis between query images and a map. This task is computation …

Visual localization, ie, camera pose estimation in a known scene, is a core component of
technologies such as autonomous driving and augmented reality. State-of-the-art …

We present an approach to solving hard geometric optimization problems in the RANSAC
framework. The hard minimal problems arise from relaxing the original geometric …

Global visual localization in LiDAR-maps, crucial for autonomous driving applications,
remains largely unexplored due to the challenging issue of bridging the cross-modal …

RANSAC-based algorithms are the standard techniques for robust estimation in computer
vision. These algorithms are iterative and computationally expensive; they alternate …

Many computer vision applications require robust estimation of the underlying geometry, in
terms of camera motion and 3D structure of the scene. These robust methods often rely on …

We present a complete classification of all minimal problems for generic arrangements of
points and lines completely observed by calibrated perspective cameras. We show that …