43 citations · 104 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Learning When to Speak: Latency and Quality Trade-offs for Simultaneous Speech-to-Speech Translation with Offline Models
Liam Dugan, Anshul Wadhawan, Kyle Spence +3
Recent work in speech-to-speech translation (S2ST) has focused primarily on offline settings, where the full input utterance is available before any output is given. This, however,…
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…
Combining Active and Passive Simulations for Secondary Motion
James F. O'Brien, Victor B. Zordan, Jessica K. Hodgins
Objects that move in response to the actions of a main character often make an important contribution to the visual richness of an animated scene. We use the term "secondary motion…