Multi-view stereo reconstruction (MVS) in the wild requires to first estimate the camera
intrinsic and extrinsic parameters. These are usually tedious and cumbersome to obtain yet …

Feature matching is an important computer vision task that involves estimating
correspondences between two images of a 3D scene and dense methods estimate all such …

Camera pose estimation in known scenes is a 3D geometry task recently tackled by multiple
learning algorithms. Many regress precise geometric quantities, like poses or 3D points …

Learning-based visual relocalizers exhibit leading pose accuracy, but require hours or days
of training. Since training needs to happen on each new scene again, long training times …

Given two images we can estimate the relative camera pose between them by establishing
image-to-image correspondences. Usually correspondences are 2D-to-2D and the pose we …

We describe a learning-based system that estimates the camera position and orientation
from a single input image relative to a known environment. The system is flexible wrt the …

We address the task of estimating camera parameters from a set of images depicting a
scene. Popular feature-based structure-from-motion (SfM) tools solve this task by …

Scene coordinate regression (SCR) methods are a family of visual localization methods that
directly regress 2D-3D matches for camera pose estimation. They are effective in small …

Pose regression networks predict the camera pose of a query image relative to a known
environment. Within this family of methods absolute pose regression (APR) has recently …