13 citations
- American Institute of Aeronautics and AstronauticsUS1 paper
- Austrian Institute of TechnologyAT1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Graz University of TechnologyAT1 paper
- Institut de Mathématiques de BordeauxFR1 paper
- Johannes Gutenberg University MainzDE1 paper
- Jönköping UniversitySE1 paper
- KU LeuvenBE1 paper
- Lund UniversitySE1 paper
- Massachusetts Institute of TechnologyUS1 paper
- Norwegian University of Science and TechnologyNO1 paper
- NXP (Germany)DE1 paper
9 papers
Fast Iterative Five point Relative Pose Estimation
Johan Hedborg, Michael Felsberg
Robust estimation of the relative pose between two cameras is a fundamental part of Structure and Motion methods. For calibrated cameras, the five point method together with a robu…
Online Learning of Correspondences between Images
Michael Felsberg, Fredrik Larsson, Johan Wiklund +2
We propose a novel method for iterative learning of point correspondences between image sequences. Points moving on surfaces in 3D space are projected into two images. Given a poin…
Distractor-Aware Video Object Segmentation
Andreas Robinson, Abdelrahman Eldesokey, Michael Felsberg
Semi-supervised video object segmentation is a challenging task that aims to segment a target throughout a video sequence given an initial mask at the first frame. Discriminative a…
Representative Sets in Propositional Abduction
Johannes Schmidt, Mohamed Maizia, Victor Lagerkvist +1
The propositional abduction problem is a well-known form of non-monotonic reasoning where we are asked to find an explanation of a given manifestation. Recently, there has been an…
Stability of the Active Flux Method in the Framework of Summation-by-Parts Operators
Wasilij Barsukow, Christian Klingenberg, Lisa Lechner +3
The Active Flux method is a numerical method for conservation laws using a combination of cell averages and point values as independent degrees of freedom, based on ideas from fini…
Efficient sampling for sparse Bayesian learning using hierarchical prior normalization
Jan Glaubitz, Youssef Marzouk
We introduce an approach for efficient Markov chain Monte Carlo (MCMC) sampling for challenging high-dimensional distributions in sparse Bayesian learning (SBL). The core innovatio…