166 citations · 757 across the 41 of their papers we have counts for
10 papers · 1 filter
Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve
Thomas Schöps, Viktor Larsson, Marc Pollefeys +1
Camera calibration is an essential first step in setting up 3D Computer Vision systems. Commonly used parametric camera models are limited to a few degrees of freedom and thus ofte…
Is This The Right Place? Geometric-Semantic Pose Verification for Indoor Visual Localization
Hajime Taira, Ignacio Rocco, Jiri Sedlar +5
Visual localization in large and complex indoor scenes, dominated by weakly textured rooms and repeating geometric patterns, is a challenging problem with high practical relevance…
Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization
Måns Larsson, Erik Stenborg, Carl Toft +3
Long-term visual localization is the problem of estimating the camera pose of a given query image in a scene whose appearance changes over time. It is an important problem in pract…
To Learn or Not to Learn: Visual Localization from Essential Matrices
Qunjie Zhou, Torsten Sattler, Marc Pollefeys +1
Visual localization is the problem of estimating a camera within a scene and a key component in computer vision applications such as self-driving cars and Mixed Reality. State-of-t…
Large-scale, real-time visual-inertial localization revisited
Simon Lynen, Bernhard Zeisl, Dror Aiger +5
The overarching goals in image-based localization are scale, robustness and speed. In recent years, approaches based on local features and sparse 3D point-cloud models have both do…
D2-Net: A Trainable CNN for Joint Detection and Description of Local Features
Mihai Dusmanu, Ignacio Rocco, Tomas Pajdla +4
In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions. We propose an approach where a single convolutional neural n…