1 code implementation • 26 Sep 2023 • Thomas Monninger, Andreas Weber, Steffen Staab
We show the effectiveness of basic statistical approaches for this task by implementing and evaluating a pattern-based contribution method.
no code implementations • 13 Dec 2019 • Julian Tanke, Oh-Hun Kwon, Patrick Stotko, Radu Alexandru Rosu, Michael Weinmann, Hassan Errami, Sven Behnke, Maren Bennewitz, Reinhard Klein, Andreas Weber, Angela Yao, Juergen Gall
The key prerequisite for accessing the huge potential of current machine learning techniques is the availability of large databases that capture the complex relations of interest.
no code implementations • 13 Dec 2019 • Kristina Enes, Hassan Errami, Moritz Wolter, Tim Krake, Bernhard Eberhardt, Andreas Weber, Jörg Zimmermann
Exploring the influence of the number of delays on the reconstruction and prediction of various motion classes, we show that the anticipation errors in our results are comparable or even better for very short anticipation times ($<0. 4$ sec) to a recurrent neural network based method.
no code implementations • 12 Dec 2019 • Julian Tanke, Andreas Weber, Juergen Gall
We exploit this connection by first anticipating symbolic labels and then generate human motion, conditioned on the human motion input sequence as well as on the forecast labels.
no code implementations • 9 Oct 2019 • Dima Grigoriev, Alexandru Iosif, Hamid Rahkooy, Thomas Sturm, Andreas Weber
We present algorithms and computations on 129 models from the BioModels repository testing for group and coset structures over both the complex numbers and the real numbers.
no code implementations • 8 May 2017 • Umar Iqbal, Andreas Doering, Hashim Yasin, Björn Krüger, Andreas Weber, Juergen Gall
To this end, we first convert the motion capture data into a normalized 2D pose space, and separately learn a 2D pose estimation model from the image data.
Ranked #37 on Monocular 3D Human Pose Estimation on Human3.6M
no code implementations • 22 Oct 2015 • Björn Krüger, Anna Vögele, Tobias Willig, Angela Yao, Reinhard Klein, Andreas Weber
We introduce a method for automated temporal segmentation of human motion data into distinct actions and compositing motion primitives based on self-similar structures in the motion sequence.
no code implementations • CVPR 2016 • Hashim Yasin, Umar Iqbal, Björn Krüger, Andreas Weber, Juergen Gall
To integrate both sources, we propose a dual-source approach that combines 2D pose estimation with efficient and robust 3D pose retrieval.
Ranked #22 on 3D Human Pose Estimation on HumanEva-I