384 citations · 433 across the 3 of their papers we have counts for
3 papers
cs.GR2023★ 22 cited
AdaptNet: Policy Adaptation for Physics-Based Character Control
Pei Xu, Kaixiang Xie, Sheldon Andrews +5
Motivated by humans' ability to adapt skills in the learning of new ones, this paper presents AdaptNet, an approach for modifying the latent space of existing policies to allow new…
cs.GR2023★ 27 cited
Composite Motion Learning with Task Control
Pei Xu, Xiumin Shang, Victor Zordan +1
We present a deep learning method for composite and task-driven motion control for physically simulated characters. In contrast to existing data-driven approaches using reinforceme…
physics.soc-ph2014★ 384 cited
Universal power law governing pedestrian interactions
Ioannis Karamouzas, Brian Skinner, Stephen J. Guy
Human crowds often bear a striking resemblance to interacting particle systems, and this has prompted many researchers to describe pedestrian dynamics in terms of interaction force…