69 citations · 70 across the 3 of their papers we have counts for
4 papers
Learning Realistic Athletic Sprinting Without Demonstrations
William Wang, Nicholas Bianco, Guy Tevet +4
We present a muscle-driven simulation system for generating biomechanically accurate motion for high-speed athletic locomotion tasks that does not require motion demonstrations. Ou…
MUSIC: Learning Muscle-Driven Dexterous Hand Control
Pei Xu, Yufei Ye, Shuchun Sun +3
We present a data-driven approach for physics-based, muscle-driven dexterous control that enables musculoskeletal hands to perform precise piano playing for novel pieces of music o…
From Skin to Skeleton: Towards Biomechanically Accurate 3D Digital Humans
Marilyn Keller, Keenon Werling, Soyong Shin +4
Great progress has been made in estimating 3D human pose and shape from images and video by training neural networks to directly regress the parameters of parametric human models l…
AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale
Keenon Werling, Janelle Kaneda, Alan Tan +15
While reconstructing human poses in 3D from inexpensive sensors has advanced significantly in recent years, quantifying the dynamics of human motion, including the muscle-generated…