Yingjie Zhou, Zicheng Zhang, Jun Jia, Yanwei Jiang, Xiaohong Liu, Xiongkuo Min and Guangtao Zhai
Email: zyj2000@sjtu.edu.cn
This repository explores the fascinating question of imitation capabilities across different models. We investigate various approaches to motion imitation and evaluate their effectiveness in replicating complex human movements. Our work provides insights into the fundamental differences between imitation learning paradigms.
Figure 1: Comparative visualization of different imitation approaches.
Our novel Peer-to-Peer Motion (P2P-Motion) framework establishes a new benchmark in imitation learning. Key features include:
- Real-time motion transfer between heterogeneous agents
- Adaptive spatial-temporal alignment
- Bidirectional imitation capability
- Robustness to morphological differences
To use this Dataset:
To use sources in Dataset (including Designed Animation and Generated Human Images):
git clone https://github.com/yourusername/who-is-a-better-imitator.git
cd who-is-a-better-imitator
pip install -r requirements.txt