Now showing items 1-2 of 2

    • Learning and Exploring Motor Skills with Spacetime Bounds 

      Ma, Li-Ke; Yang, Zeshi; Tong, Xin; Guo, Baining; Yin, KangKang (The Eurographics Association and John Wiley & Sons Ltd., 2021)
      Equipping characters with diverse motor skills is the current bottleneck of physics-based character animation. We propose a Deep Reinforcement Learning (DRL) framework that enables physics-based characters to learn and ...
    • MultiResGNet: Approximating Nonlinear Deformation via Multi-Resolution Graphs 

      Li, Tianxing; Shi, Rui; Kanai, Takashi (The Eurographics Association and John Wiley & Sons Ltd., 2021)
      This paper presents a graph-learning-based, powerfully generalized method for automatically generating nonlinear deformation for characters with an arbitrary number of vertices. Large-scale character datasets with a ...