no code implementations • 17 Mar 2024 • Xiaohan Zhang, Bharat Lal Bhatnagar, Sebastian Starke, Ilya Petrov, Vladimir Guzov, Helisa Dhamo, Eduardo Pérez-Pellitero, Gerard Pons-Moll
Our key insight is that human motion is dictated by the interrelation between the force exerted by the human and the perceived resistance.
no code implementations • 19 Sep 2023 • Qasim M. K. Siddiqui, Sebastian Starke, Peter Steinbach
Two distinct clustering approaches are evaluated which compute spatial and fractional certainty per instance employing samples by the Monte-Carlo Dropout or Deep Ensemble technique.
1 code implementation • 24 Aug 2023 • Paul Starke, Sebastian Starke, Taku Komura, Frank Steinicke
This paper introduces a novel data-driven motion in-betweening system to reach target poses of characters by making use of phases variables learned by a Periodic Autoencoder.
no code implementations • 9 Jun 2023 • Sunmin Lee, Sebastian Starke, Yuting Ye, Jungdam Won, Alexander Winkler
Most existing methods for motion tracking avoid environment interaction apart from foot-floor contact due to their complex dynamics and hard constraints.
1 code implementation • CVPR 2023 • Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
A particular challenge is that only a sparse tracking signal is available from standalone HMDs (Head Mounted Devices), often limited to tracking the user's head and wrists.
no code implementations • ICCV 2023 • Mingyi Shi, Sebastian Starke, Yuting Ye, Taku Komura, Jungdam Won
We present a novel motion prior, called PhaseMP, modeling a probability distribution on pose transitions conditioned by a frequency domain feature extracted from a periodic autoencoder.
1 code implementation • SIGGRAPH 2022 • Zhaoming Xie, Sebastian Starke, Hung Yu Ling, Michiel Van de Panne
Learning physics-based character controllers that can successfully integrate diverse motor skills using a single policy remains a challenging problem.
no code implementations • 1 May 2022 • Xiaohan Zhang, Bharat Lal Bhatnagar, Vladimir Guzov, Sebastian Starke, Gerard Pons-Moll
In this work, we study the problem of synthesizing scene interactions conditioned on different contact positions on the object.
1 code implementation • 11 Apr 2022 • Peter Steinbach, Felicita Gernhardt, Mahnoor Tanveer, Steve Schmerler, Sebastian Starke
With the availability of data, hardware, software ecosystem and relevant skill sets, the machine learning community is undergoing a rapid development with new architectures and approaches appearing at high frequency every year.
no code implementations • 7 Feb 2022 • Hendrik Hessenkemper, Sebastian Starke, Yazan Atassi, Thomas Ziegenhein, Dirk Lucas
An automated and reliable processing of bubbly flow images is highly needed to analyse large data sets of comprehensive experimental series.
1 code implementation • 12 Jan 2022 • Ian Mason, Sebastian Starke, Taku Komura
In this work we present a style modelling system that uses an animation synthesis network to model motion content based on local motion phases.