activity
20232026
most citedPADL: Language-Directed Physics-Based Character Control

30 citations · 38 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

GPC: Large-Scale Generative Pretraining for Transferable Motor Control

Yi Shi, Yifeng Jiang, Chen Tessler +1

Developing controllers capable of completing a wide range of tasks in a natural and life-like manner is a key challenge in enabling practical applications of physics-based characte…

cs.CV2025

SHARE: Scene-Human Aligned Reconstruction

Joshua Li, Brendan Chharawala, Chang Shu +2

Animating realistic character interactions with the surrounding environment is important for autonomous agents in gaming, AR/VR, and robotics. However, current methods for human mo…

cs.GR2025

HIL: Hybrid Imitation Learning of Diverse Parkour Skills from Videos

Jiashun Wang, Yifeng Jiang, Haotian Zhang +4

Data-driven methods leveraging deep reinforcement learning have become the dominant paradigm for developing controllers that enable physically simulated characters to produce natur…

cs.CV2025

StableMotion: Training Motion Cleanup Models with Unpaired Corrupted Data

Yuxuan Mu, Hung Yu Ling, Yi Shi +5

Motion capture (mocap) data often exhibits visually jarring artifacts due to inaccurate sensors and post-processing. Cleaning this corrupted data can require substantial manual eff…

cs.LG2024★ 5 cited

SuperPADL: Scaling Language-Directed Physics-Based Control with Progressive Supervised Distillation

Jordan Juravsky, Yunrong Guo, Sanja Fidler +1

Physically-simulated models for human motion can generate high-quality responsive character animations, often in real-time. Natural language serves as a flexible interface for cont…

cs.CV2023★ 3 cited

Interactive Character Control with Auto-Regressive Motion Diffusion Models

Yi Shi, Jingbo Wang, Xuekun Jiang +3

Real-time character control is an essential component for interactive experiences, with a broad range of applications, including physics simulations, video games, and virtual reali…

cs.LG2023★ 30 cited

PADL: Language-Directed Physics-Based Character Control

Jordan Juravsky, Yunrong Guo, Sanja Fidler +1

Developing systems that can synthesize natural and life-like motions for simulated characters has long been a focus for computer animation. But in order for these systems to be use…