no code implementations • 4 Apr 2023 • Jubo Yu, Tianxiang Ren, Shihui Guo, Fengyi Fang, Kai Wang, Zijiao Zeng, Yazhan Zhang, Andreas Aristidou, Yipeng Qin
In this paper, we follow a data-centric philosophy and propose a novel motion annotation method based on the inherent representativeness of motion data in a given dataset.
no code implementations • 25 Mar 2023 • Tianxiang Ren, Jubo Yu, Shihui Guo, Ying Ma, Yutao Ouyang, Zijiao Zeng, Yazhan Zhang, Yipeng Qin
In-betweening is a technique for generating transitions given initial and target character states.
no code implementations • 9 Apr 2021 • Weihao Yuan, Yazhan Zhang, Bingkun Wu, Siyu Zhu, Ping Tan, Michael Yu Wang, Qifeng Chen
Self-supervised learning for depth estimation possesses several advantages over supervised learning.
no code implementations • 9 Oct 2019 • Yazhan Zhang, Weihao Yuan, Zicheng Kan, Michael Yu Wang
In essence, successful grasp boils down to correct responses to multiple contact events between fingertips and objects.
1 code implementation • 5 Oct 2018 • Yazhan Zhang, Zicheng Kan, Yu Alexander Tse, Yang Yang, Michael Yu Wang
Tactile sensing is essential to the human perception system, so as to robot.