119 citations · 297 across the 17 of their papers we have counts for
4 papers · 1 filter
Leveraging Demonstrations with Latent Space Priors
Jonas Gehring, Deepak Gopinath, Jungdam Won +3
Demonstrations provide insight into relevant state or action space regions, bearing great potential to boost the efficiency and practicality of reinforcement learning agents. In th…
QuestSim: Human Motion Tracking from Sparse Sensors with Simulated Avatars
Alexander Winkler, Jungdam Won, Yuting Ye
Real-time tracking of human body motion is crucial for interactive and immersive experiences in AR/VR. However, very limited sensor data about the body is available from standalone…
Transformer Inertial Poser: Real-time Human Motion Reconstruction from Sparse IMUs with Simultaneous Terrain Generation
Yifeng Jiang, Yuting Ye, Deepak Gopinath +3
Real-time human motion reconstruction from a sparse set of (e.g. six) wearable IMUs provides a non-intrusive and economic approach to motion capture. Without the ability to acquire…
Conditional Motion In-betweening
Jihoon Kim, Taehyun Byun, Seungyoun Shin +2
Motion in-betweening (MIB) is a process of generating intermediate skeletal movement between the given start and target poses while preserving the naturalness of the motion, such a…