no code implementations • 29 Aug 2023 • Lei Han, Qingxu Zhu, Jiapeng Sheng, Chong Zhang, Tingguang Li, Yizheng Zhang, He Zhang, Yuzhen Liu, Cheng Zhou, Rui Zhao, Jie Li, Yufeng Zhang, Rui Wang, Wanchao Chi, Xiong Li, Yonghui Zhu, Lingzhu Xiang, Xiao Teng, Zhengyou Zhang
In this work, we propose a framework for driving legged robots act like real animals with lifelike agility and strategy in complex environments.
no code implementations • 13 Jun 2022 • Jiawei Xu, Cheng Zhou, Yizheng Zhang, Baoxiang Wang, Lei Han
Integrating the two algorithms results in the complete Relative Policy-Transition Optimization (RPTO) algorithm, in which the policy interacts with the two environments simultaneously, such that data collections from two environments, policy and transition updates are completed in one closed loop to form a principled learning framework for policy transfer.
no code implementations • 30 Mar 2022 • Yingtian Tang, Jiangtao Liu, Cheng Zhou, Tingguang Li
Motion style transfer is highly desired for motion generation systems for gaming.
no code implementations • 29 Sep 2021 • Lei Han, Cheng Zhou, Yizheng Zhang
We propose a new general theory measuring the relativity between two arbitrary Markov Decision Processes (MDPs) from the perspective of reinforcement learning (RL).
no code implementations • ICCV 2021 • Piaopiao Yu, Jie Guo, Fan Huang, Cheng Zhou, Hongwei Che, Xiao Ling, Yanwen Guo
However, naively compressing an outdoor panorama into a low-dimensional latent vector, as existing models have done, causes two major problems.
no code implementations • 19 Jun 2019 • Mingjie Li, Youqian Feng, Zhonghai Yin, Cheng Zhou, Fanghao Dong, Yu-an Lin, Yuhao Dong
Meanwhile, the action recognition network is tested in our gesture and body posture data sets for specific target.
no code implementations • 18 Jun 2019 • Mingjie Li, Youqian Feng, Zhonghai Yin, Cheng Zhou, Fanghao Dong
Common target detection is usually based on single frame images, which is vulnerable to affected by the similar targets in the image and not applicable to video images.
1 code implementation • ICLR 2019 • Meng Fang, Cheng Zhou, Bei Shi, Boqing Gong, Jia Xu, Tong Zhang
Dealing with sparse rewards is one of the most important challenges in reinforcement learning (RL), especially when a goal is dynamic (e. g., to grasp a moving object).
no code implementations • 11 Feb 2015 • Cheng Zhou, Fang Han, Xinsheng Zhang, Han Liu
Theoretically, we develop a theory for testing the equality of U-statistic based correlation matrices.