85 citations · 141 across the 8 of their papers we have counts for
8 papers
Motion In-Betweening with Phase Manifolds
Paul Starke, Sebastian Starke, Taku Komura +1
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. Our a…
Hierarchical Planning and Control for Box Loco-Manipulation
Zhaoming Xie, Jonathan Tseng, Sebastian Starke +2
Humans perform everyday tasks using a combination of locomotion and manipulation skills. Building a system that can handle both skills is essential to creating virtual humans. We p…
QuestEnvSim: Environment-Aware Simulated Motion Tracking from Sparse Sensors
Sunmin Lee, Sebastian Starke, Yuting Ye +2
Replicating a user's pose from only wearable sensors is important for many AR/VR applications. Most existing methods for motion tracking avoid environment interaction apart from fo…
Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola +3
With the recent surge in popularity of AR/VR applications, realistic and accurate control of 3D full-body avatars has become a highly demanded feature. A particular challenge is th…
COUCH: Towards Controllable Human-Chair Interactions
Xiaohan Zhang, Bharat Lal Bhatnagar, Vladimir Guzov +2
Humans interact with an object in many different ways by making contact at different locations, creating a highly complex motion space that can be difficult to learn, particularly…
Machine Learning State-of-the-Art with Uncertainties
Peter Steinbach, Felicita Gernhardt, Mahnoor Tanveer +2
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 app…
Bubble identification from images with machine learning methods
Hendrik Hessenkemper, Sebastian Starke, Yazan Atassi +2
An automated and reliable processing of bubbly flow images is highly needed to analyse large data sets of comprehensive experimental series. A particular difficulty arises due to o…
Real-Time Style Modelling of Human Locomotion via Feature-Wise Transformations and Local Motion Phases
Ian Mason, Sebastian Starke, Taku Komura
Controlling the manner in which a character moves in a real-time animation system is a challenging task with useful applications. Existing style transfer systems require access to…