In computer vision applications, the following problem often arises: Giv...
Most state-of-the-art localization algorithms rely on robust relative po...
AR/VR applications and robots need to know when the scene has changed. A...
We propose a new method for constructing elimination templates for effic...
We present an approach to solving hard geometric optimization problems i...
We present a technique for a complete 3D reconstruction of small objects...
We consider Galois/monodromy groups arising in computer vision applicati...
We present a robot kinematic calibration method that combines complement...
The Inverse Kinematics (IK) problem is to nd robot control parameters to...
Local features e.g. SIFT and its affine and learned variants provide
reg...
Most consumer cameras are equipped with electronic rolling shutter, lead...
The internal geometry of most modern consumer cameras is not adequately
...
We present a complete classification of minimal problems for generic
arr...
Visual localization in large and complex indoor scenes, dominated by wea...
In this paper we address a classification problem that has not been
cons...
In this work we address the problem of finding reliable pixel-level
corr...
We present a complete classification of all minimal problems for generic...
We present a new minimal problem for relative pose estimation mixing poi...
This paper presents new efficient solutions to the rolling shutter camer...
We address the problem of finding reliable dense correspondences between...
Estimating uncertainty of camera parameters computed in Structure from M...
We seek to predict the 6 degree-of-freedom (6DoF) pose of a query photog...
Many computer vision applications require robust estimation of the under...
Visual localization enables autonomous vehicles to navigate in their
sur...
We present a new insight into the systematic generation of minimal solve...
The distortion varieties of a given projective variety are parametrized ...
In this paper, we propose an algebraic approach to upgrade a projective
...