2 citations · 2 across the 4 of their papers we have counts for
5 papers
Learning and Sequencing of Object-Centric Manipulation Skills for Industrial Tasks
Leonel Rozo, Meng Guo, Andras G. Kupcsik +8
Enabling robots to quickly learn manipulation skills is an important, yet challenging problem. Such manipulation skills should be flexible, e.g., be able adapt to the current works…
SDNet: Semantically Guided Depth Estimation Network
Matthias Ochs, Adrian Kretz, Rudolf Mester
Autonomous vehicles and robots require a full scene understanding of the environment to interact with it. Such a perception typically incorporates pixel-wise knowledge of the depth…
DistanceNet: Estimating Traveled Distance from Monocular Images using a Recurrent Convolutional Neural Network
Robin Kreuzig, Matthias Ochs, Rudolf Mester
Classical monocular vSLAM/VO methods suffer from the scale ambiguity problem. Hybrid approaches solve this problem by adding deep learning methods, for example by using depth maps…
Joint Epipolar Tracking (JET): Simultaneous optimization of epipolar geometry and feature correspondences
Henry Bradler, Matthias Ochs, Rudolf Mester
Traditionally, pose estimation is considered as a two step problem. First, feature correspondences are determined by direct comparison of image patches, or by associating feature d…
Learning Rank Reduced Interpolation with Principal Component Analysis
Matthias Ochs, Henry Bradler, Rudolf Mester
In computer vision most iterative optimization algorithms, both sparse and dense, rely on a coarse and reliable dense initialization to bootstrap their optimization procedure. For…