[About Me]

Libin Liu

Assistant Professor

Center on Frontiers of Computing Studies
Peking University

Email: libin.liu [at] pku.edu.cn

I am an assistant professor at Center on Frontiers of Computing Studies, Peking University. Before joining Peking University, I was the Chief Scientist of DeepMotion Inc. I was a postdoctoral research fellow at Disney Research and the University of British Columbia. I recieved my Ph.D. degree in computer science in 2014 and my B.S. degree in mathematics and physics in 2009, both from Tsinghua University.

I am interested in character animation, physics-based simulation, motion control, and related areas such as optimal control, reinforcement learning, deep learning, and robotics. I put a lot of work into realizing various agile human motions on simulated characters and robots.

[Projects]

Learning Basketball Dribbling Skills Using Trajectory Optimization and Deep Reinforcement Learning

Libin Liu, Jessica K. Hodgins

We present a method based on trajectory optimization and deep reinforcement learning for learning robust controllers for various basketball dribbling skills, such as dribbling between the legs, running, and crossovers.

ACM Transactions on Graphics, Vol 37 Issue 4, Article 142 (SIGGRAPH 2018). (to appear)

Learning to Schedule Control Fragments for Physics-Based Characters Using Deep Q-Learning

Libin Liu, Jessica K. Hodgins

We present a deep Q-learning based method for learning a scheduling scheme that reorders short control fragments as necessary at runtime to achieve robust control of challenging skills such as skateboarding.

ACM Transactions on Graphics, Vol 36 Issue 3, Article 29. (presented at SIGGRAPH 2017)

Guided Learning of Control Graphs for Physics-Based Characters

Libin Liu, Michiel van de Panne, KangKang Yin,

We present a method for learning robust control graphs that support real-time physics-based simulation of multiple characters, each capable of a diverse range of movement skills.

ACM Transactions on Graphics, Vol 35, Issue 2, Article 29. (presented at SIGGRAPH 2016)

Learning Reduced-Order Feedback Policies for Motion Skills

Kai Ding, Libin Liu, Michiel van de Panne, KangKang Yin,

Proc. ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2015 (SCA Best Paper Award)

Deformation Capture and Modeling of Soft Objects

Bin Wang, Longhua Wu, KangKang Yin, Uri Ascher, Libin Liu, Hui Huang.

ACM Transactions on Graphics, Vol 34, Issue 4, Article 94 (SIGGRAPH 2015)

Improving Sampling-based Motion Control

Libin Liu, KangKang Yin, Baining Guo.

We address several limitations of the sampling-based motion control method. A variety of highly agile motions, ranging from stylized walking and dancing to gymnastic and Martial Arts routines, can be easily reconstructed now.

Computer Graphics Forum 34(2) (Eurographics 2015).

Simulation and Control of Skeleton-driven Soft Body Characters

Libin Liu, KangKang Yin, Bin Wang, Baining Guo.

We present a physics-based framework for simulation and control of human-like skeleton-driven soft body characters. We propose a novel pose-based plasticity model to achieve large skin deformation around joints. We further reconstruct controls from reference trajectories captured from human subjects by augmenting a sampling-based algorithm.

ACM Transactions on Graphics, Vol 32, Issue 6, Article 215 (SIGGRAPH Asia 2013)

Terrain Runner: Control, Parameterization, Composition, and Planning for Highly Dynamic Motions

Libin Liu, KangKang Yin, Michiel van de Panne, Baining Guo.

We present methods for the control, parameterization, composition, and planning for highly dynamic motions. More specifically, we learn the skills required by real-time physics-based avatars to perform parkour-style fast terrain crossing using a mix of running, jumping, speed-vaulting, and drop-rolling.

ACM Transactions on Graphics, Vol 31, Issue 6, Article 154 (SIGGRAPH Asia 2012)

Sampling-based Contact-rich Motion Control

Libin Liu, KangKang Yin, Michiel van de Panne, Tianjia Shao Weiwei Xu.

Given a motion capture trajectory, we propose to extract its control by randomized sampling.

ACM Transactions on Graphics, Vol 29, Issue 4, Article 128 (SIGGRAPH 2010)

[Professional Activities]
Program Committee:
  • SIGGRAPH 2019, 2020
  • Pacific Graphics 2018, 2019
  • Eurographics Short Papers 2020, 2021
  • SIGGRAPH Asia 2014 Posters and Technical Briefs
  • ACM SIGGRAPH/Eurographics Symposium on Computer Animation 2015-2019
  • ACM SIGGRAPH Conference on Motion, Interaction and Games (MIG) 2014, 2016-2019
Paper Reviewing:
  • SIGGRAPH
  • SIGGRAPH Asia
  • ACM Transactions on Graphics (TOG)
  • IEEE Transactions on Visualization and Computer Graphics (TVCG)
  • Eurographics (Eupopean Association for Computer Graphics)
  • Computer Graphics Forum
  • IEEE International Conference on Robotics and Automation (ICRA)
  • ACM SIGGRAPH/Eurographics Symposium on Computer Animation
  • ACM SIGGRAPH Conference on Motion, Interaction and Games (MIG)
  • CASA (Computer Animation and Social Agents)
  • Computers & Graphics
  • Graphical Models