Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning

no code implementations • 9 Oct 2020 • Daniele Reda, Tianxin Tao, Michiel Van de Panne

Learning to locomote is one of the most common tasks in physics-based animation and deep reinforcement learning (RL).

reinforcement-learning Reinforcement Learning (RL)

Style-ERD: Responsive and Coherent Online Motion Style Transfer

no code implementations • CVPR 2022 • Tianxin Tao, Xiaohang Zhan, Zhongquan Chen, Michiel Van de Panne

Motion style transfer is a common method for enriching character animation.

Motion Style Transfer Style Transfer

Evaluating Vision Transformer Methods for Deep Reinforcement Learning from Pixels

no code implementations • 11 Apr 2022 • Tianxin Tao, Daniele Reda, Michiel Van de Panne

Vision Transformers (ViT) have recently demonstrated the significant potential of transformer architectures for computer vision.

Contrastive Learning reinforcement-learning +1

Learning to Get Up

1 code implementation • 30 Apr 2022 • Tianxin Tao, Matthew Wilson, Ruiyu Gou, Michiel Van de Panne

Finally, a third stage learns control policies that can reproduce the weaker get-up motions at much slower speeds.