907 citations · 3.2k across the 27 of their papers we have counts for
6 papers · 1 filter
Video Prediction Models as Rewards for Reinforcement Learning
Alejandro Escontrela, Ademi Adeniji, Wilson Yan +6
Specifying reward signals that allow agents to learn complex behaviors is a long-standing challenge in reinforcement learning. A promising approach is to extract preferences for be…
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters
Chen Tessler, Yoni Kasten, Yunrong Guo +3
In this work, we present Conditional Adversarial Latent Models (CALM), an approach for generating diverse and directable behaviors for user-controlled interactive virtual character…
Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion
Davis Rempe, Zhengyi Luo, Xue Bin Peng +5
We introduce a method for generating realistic pedestrian trajectories and full-body animations that can be controlled to meet user-defined goals. We draw on recent advances in gui…
RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning
Kevin Zakka, Philipp Wu, Laura Smith +8
Replicating human-like dexterity in robot hands represents one of the largest open problems in robotics. Reinforcement learning is a promising approach that has achieved impressive…
Synthesizing Physical Character-Scene Interactions
Mohamed Hassan, Yunrong Guo, Tingwu Wang +3
Movement is how people interact with and affect their environment. For realistic character animation, it is necessary to synthesize such interactions between virtual characters and…
Robust and Versatile Bipedal Jumping Control through Reinforcement Learning
Zhongyu Li, Xue Bin Peng, Pieter Abbeel +3
This work aims to push the limits of agility for bipedal robots by enabling a torque-controlled bipedal robot to perform robust and versatile dynamic jumps in the real world. We pr…