Michiel van de Panne Projects and Publications home page
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2024 |
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PartwiseMPC: Interactive Control of Contact-Guided Motions Niloofar Khosiyar, Ruiyu Gou, Teo Zhou, Sheldon Andrews, Michiel van de Panne 2024 ACM SIGGRAPH/EG Symposium on Computer Animation project page |
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Learning-based Legged Locomotion: State of the Art and Future Perspectives Sehoon Ha, Joonho Lee, Michiel van de Panne, Zhaoming Xie, Wenhao Yu, Majid Khadiv arXiv arXiv page |
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Flexible Motion In-betweening with Diffusion Models Setareh Cohan, Guy Tevet, Daniele Reda, Xue Bin Peng, Michiel van de Panne ACM SIGGRAPH 2024 project page |
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2023 |
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Physical Simulation of Balance Recovery after a Push Alexis Jensen, Thomas Chatagnon, Niloofar Khoshsiyar, Daniele Reda, Michiel van de Panne, Charles Pontonnier, Julien Pettre MIG 2023, appearing in: Proceedings of the 16th ACM SIGGRAPH Conference on Motion, Interaction and Games Paper video; ACM Digital Library |
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Physics-based Motion Retargeting from Sparse Inputs Daniele Reda, Jungdam Won, Yuting Ye, Michiel van de Panne, Alexander Winkler SCA 2023, appearing in: Proceedings of the ACM on Computer Graphics and Interactive Techniques, Volume 6 Issue 3 project page Paper (arXiv) Video (YouTube) ACM Digital Library |
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Hierarchical Planning and Control for Box Loco-Manipulation Zhaoming Xie, Jonathan Tseng, Sebastian Starke, Michiel van de Panne, C Karen Liu SCA 2023, appearing in: Proceedings of the ACM on Computer Graphics and Interactive Techniques, Volume 6 Issue 3 Paper (PDF) Video (YouTube) Code ACM Digital Library |
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OPT-Mimic: Imitation of Optimized Trajectories for Dynamic Quadruped Behaviors Yuni Fuchioka, Zhaoming Xie, Michiel van de Panne IEEE International Conference on Robotics and Automation (ICRA 2023) project page |
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2022 |
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Understanding the Evolution of Linear Regions in Deep Reinforcement Learning Setareh Cohan, Nam Hee Kim, David Rolnick, Michiel van de Panne NeurIPS 2022 arXiv project page Code |
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Evaluating Vision Transformer Methods for Deep Reinforcement Learning from Pixels Tianxin Tao, Daniele Reda, Michiel van de Panne ICRA 2022 Workshop on Scalable Robot Learning arXiV |
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Learning Soccer Juggling Skills with Layer-wise Mixture-of-Experts Zhaoming Xie, Sebastian Starke, Hung Yu Ling, Michiel van de Panne ACM SIGGRAPH 2022 project page |
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Learning to Get Up Tianxin Tao, Matthew Wilson, Ruiyu Gou, Michiel van de Panne ACM SIGGRAPH 2022 project page |
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Learning to Brachiate via Simplified Model Imitation Daniele Reda(*), Hung Yu Ling(*), Michiel van de Panne ACM SIGGRAPH 2022 project page |
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Style-erd: Responsive and coherent online motion style transfer Tianxin Tao, Xiaohang Zhan, Zhongquan Chen, and Michiel van de Panne IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2022. project page |
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A Survey on Reinforcement Learning Methods in Character Animation Ariel Kwiatkowski, Eduardo Alvarado, Vicky Kalogeiton, C Karen Liu, Julien Pettre, Michiel van de Panne, Marie-Paule Cani Computer Graphics Forum, 41(2), 2022, p613-639 |
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2021 |
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From machine learning to robotics: Challenges and opportunities for embodied intelligence Nicholas Roy, Ingmar Posner, Tim Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Dan Koditschek, Tomas Lozano-Perez, Vikash Mansinghka, Christopher Pal, Blake Richards, Dorsa Sadigh, Stefan Schaal, Gaurav Sukhatme, Denis Therien, Marc Toussaint, Michiel Van de Panne https://arxiv.org/abs/2110.15245 |
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Flexible Motion Optimization with Modulated Assistive Forces Nam Hee Kim, Hung Yu Ling, Zhaoming Xie, Michiel van de Panne ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2021, appearing in: PACM on Computer Graphics and Interactive Techniques project page |
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Learning Task-Agnostic Action Spaces for Movement Optimization Amin Babadi, Michiel van de Panne, C. Karen Liu, Perttu Hämäläinen IEEE Transactions on Computer Graphics and Visualization IEEE Open Access arXiv (combined PDF) YouTube video project page |
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GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model Zhaoming Xie, Xingye Da, Buck Babich, Animesh Garg, and Michiel van de Panne In 15th International Workshop on the Algorithmic Foundations of Robotics (WAFR). 2022. arXiv |
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Discovering Diverse Athletic Jumping Strategies Zhiqi Yin, Zeshi Yang, Michiel van de Panne, KangKang Yin ACM Transactions on Graphics (Proc SIGGRAPH 2021, to appear) arXiv project page |
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Dynamics Randomization Revisited: A Case Study for Quadrupedal Locomotion Zhaoming Xie, Xingye Da, Michiel van de Panne, Buck Babich and Animesh Garg IEEE International Conference on Robotics and Automation (ICRA 2021) arXiv project page |
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2020 |
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Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning Daniele Reda, Tianxin Tao, Michiel van de Panne ACM SIGGRAPH Motion, Interaction and Games (MIG 2020) project page |
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ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills Zhaoming Xie, Hung Yu Ling, Nam Hee Kim, Michiel van de Panne ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2020 Best Paper Award project page |
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Fast and Flexible Multilegged Locomotion Using Learned Centroidal Dynamics Taesoo Kwon, Yoonsang Lee, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2020) project page |
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Character Controllers using Motion VAEs Hung Yu Ling, Fabio Zinno, George Cheng, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2020) project page |
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Learning to correspond dynamical systems Nam Hee Kim, Zhaoming Xie, Michiel van de Panne Proceedings of Machine Learning Research (Learning for Dynamics and Control 2020) (L4DC) project page |
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2019 |
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Learning Locomotion Skills for Cassie: Iterative Design and Sim-to-Real Zhaoming Xie, Patrick Clary, Jeremy Dao, Pedro Morais, Jonathan Hurst, Michiel van de Panne Conference on Robot Learning (CORL 2019) project page |
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On Learning Symmetric Locomotion Farzad Abdolhosseini, Hung Yu Ling, Zhaoming Xie, Xue Bin Peng, Michiel van de Panne ACM SIGGRAPH Motion, Interaction, and Games 2019 (MIG 2019) Also: NeurIPS 2019 Deep Reinforcement Learning workshop. project page |
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2018 |
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Terrain RL Sim Glen Berseth, Xue Bin Peng, Michiel van de Panne We provide a simulation codebase for 88 challenging simulation environments, which include randomized terrains and egocentric perception of the terrains. The API closely follows the openAIGym style. project page |
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Data-driven Autocompletion for Keyframe Animation Xinyi Zhang, Michiel van de Panne Best Paper Award Motion, Interaction, and Games 2018 (MIG 2018) project page |
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Feedback Control for Cassie with Deep Reinforcement Learning Zhaoming Xie, Glen Berseth, Patrick Clary, Jonathan Hurst, Michiel van de Panne IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018) project page |
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Model-Based Action Exploration for Learning Dynamic Motion Skills Glen Berseth, Alex Kyriazis, Ivan Zinin, William Choi, Michiel van de Panne IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018) project page |
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DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills Xue Bin Peng, Pieter Abbeel, Sergey Levine, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2018) project page |
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Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control Glen Berseth, Cheng Xie, Paul Cernek, Michiel van de Panne International Conference on Learning Representations (ICLR 2018) project page |
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Simulation for Control KangKang Yin, Libin Liu, Michiel van de Panne In Humanoid Robotics: A Reference Ambarish Goswami and Prahlad Vadakkepat (eds), 2018, Springer (awaiting print) |
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Biped Controllers for Character Animation KangKang Yin, Stelian Coros, Michiel van de Panne In Handbook of Human Motion Bertram Muller and Sebastian Wolf (eds), 2018, Springer (awaiting print) |
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2017 |
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Learning Locomotion Skills Using DeepRL: Does the Choice of Action Space Matter? Xue Bin Peng, Michiel van de Panne Best Student Paper Award ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2017 project page |
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DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning Xue Bin Peng, Glen Berseth, KangKang Yin, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2017) project page |
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Domain of Attraction Expansion for Physics-Based Character Control Mazen Al Borno, Michiel Van De Panne, Eugene Fiume ACM Transactions on Graphics, Volume 36 Issue 2, April 2017, Article 17 |
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2016 |
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Terrain-Adaptive Locomotion Skills Using Deep Reinforcement Learning Xue Bin Peng, Glen Berseth, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2016) Additional non-archival presentations at Dynamic Walking 2016 and NIPS 2016 Deep Learning Symposium 2016 project page |
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Task-based Locomotion
Shailen Agrawal, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2016) project page |
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Guided Learning of Control Graphs for Physics-Based Characters
Libin Liu, Michiel van de Panne, KangKang Yin ACM Transactions on Graphics (presented at SIGGRAPH 2016) project page |
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Anticipatory balance control and dimension reduction
Amir Rabbani, Michiel van de Panne, Paul Kry Computer Animation and Virtual Worlds paper |
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2015 |
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Learning Reduced-Order Feedback Policies for Motion Skills Kai Ding, Libin Liu, Michiel van de Panne, KangKang Yin ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2015 Best paper project page |
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Dynamic Terrain Traversal Skills Using Reinforcement Learning Xue Bin Peng, Glen Berseth, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2015) Additional non-archival presentations of this work to be given at Dynamic Walking 2015 RLDM 2015 project page |
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Vector Graphics Animation with Time-Varying Topology Boris Dalstein, Rémi Ronfard, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2015) project page |
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Controller Design for Multiskilled Bipedal Characters Michael Firmin, Michiel van de Panne Computer Graphics Forum project page |
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2014 |
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Modeling 3D Animals from a Side-view Sketch Even Entem, Loic Barthe, Marie-Paule Cani, Frederic Cordier, Michiel van de Panne Computers & Graphics, Special Issue on Shape Modeling International 2014 project page |
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Anticipatory Balance Control Amir H. Rabbani, Michiel van de Panne, Paul G. Kry ACM SIGGRAPH Motion in Games 2014 project page |
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Vector Graphics Complexes Boris Dalstein, Remi Ronfard, Michiel van de Panne ACM Transactions on Graphics (Proc. SIGGRAPH 2014) project page |
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Poster: Towards a Control Language for Authoring Humanoid Motions Michael Firmin, Michiel van de Panne Talk: Optimizing Muscle Routing and Control for Diverse Morphologies Thomas Geijtenbeek, Michiel van de Panne, A.F. van der Stappen, F.C.T. van der Helm |
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Motion fields for interactive character animation: technical perspective Communications of the ACM Research highlights Michiel van de Panne article (one page) |
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Diverse Motions and Character Shapes for Simulated Skills IEEE Transactions on Visualization and Computer Graphics Shailen Agrawal, Shuo Shen, Michiel van de Panne (30%+ extended version of SCA 2013 paper) preprint Official version |
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2013 |
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Pareto Optimal Control for Natural and Supernatural Motions Shailen Agrawal, Michiel van de Panne Motion in Games (MIG 2013) Best paper project page |
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Flexible Muscle-Based Locomotion for Bipedal Creatures Thomas Geijtenbeek, Michiel van de Panne, A. Frank van der Stappen ACM Transactions on Graphics (Proc. SIGGRAPH ASIA 2013) project page |
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Diverse Motion Variations for Physics-based Character Animation Shailen Agrawal, Shuo Shen, Michiel van de Panne Symposium on Computer Animation (SCA 2013) Best paper honorable mention project page |
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2012 |
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Terrain Runner: Control, Parameterization, Composition, and Planning for Highly Dynamic Motions Libin Liu, KangKang Yin, Michiel van de Panne, Baining Guo ACM Transactions on Graphics (Proc. SIGGRAPH ASIA 2012) project page |
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Curriculum Learning for Motor Skills Andrej Karpathy, Michiel van de Panne Proceedings of AI 2012 project page |
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IEEE TVCG Special Section on the ACM SIGGRAPH/Eurographics Symposium on Computer Animation Adam Bargteil and Michiel van de Panne (guest editors) IEEE TVCG issue and guest editor's introduction, Aug 2012, Volume 18, Number 8 |
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2011 |
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Proceedings of ACM/Eurographics Symposium on Computer Animation 2011, Vancouver, Canada, Aug 5-7 2011 Adam Bargteil and Michiel van de Panne (program co-chairs and proceedings editors) |
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Displacement Interpolation Using Lagrangian Mass Transport Nicolas Bonneel, Michiel van de Panne, Sylvain Paris, Wolfgang Heidrich ACM Transactions on Graphics (Proc. ACM SIGGRAPH ASIA 2011). project web page This paper describes a generic method for interpolating between pairs of functions or distributions using mass transport methods. The method copes well with features that exhibit translational motion between examplars, unlike interpolation schemes that use linearly-weighted mixtures. |
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Locomotion Skills for Simulated Quadrupeds Stelian Coros, Andrej Karpathy, Benjamin Jones, Lionel Reveret, Michiel van de Panne ACM Transactions on Graphics (Proc. ACM SIGGRAPH 2011). project web page |
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2010 |
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Proxy-Guided Texture Synthesis for Rendering Natural Scenes Nicolas Bonneel, Michiel van de Panne, Sylvain Lefebvre, George Drettakis VMV 2010: Vision, Modeling, and Visualization Best Paper Award (82 submissions, 43 accepted). pdf additional material YouTube video |
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Generalized Biped Walking Control Stelian Coros, Philippe Beaudoin, Michiel van de Panne ACM Transactions on Graphics (Proc. ACM SIGGRAPH 2010). project web page |
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Sampling-based Contact-rich Motion Control Libin Liu, KangKang Yin, Michiel van de Panne, Tianjia Shao, Weiwei Xu ACM Transactions on Graphics (Proc. ACM SIGGRAPH 2010). project web page |
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Flexible Isosurfaces: Simplifying and Displaying Scalar Topology Using the Contour Tree Hamish Carr, Jack Snoeyink, Michiel van de Panne Computational Geometry, 43(1), 2010, p. 42-58 |
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2009 |
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Robust Task-based Control Policies for Physics-based Characters Stelian Coros, Philippe Beaudoin, Michiel van de Panne ACM Transactions on Graphics (Proc. ACM SIGGRAPH ASIA 2009). project web page code for SIMBICON controller editor and simulation |
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Joint-aware Manipulation of Deformable Models Weiwei Xu, Jun Wang, KangKang Yin, Kun Zhou, Michiel van de Panne, Falai Chen, Baining Guo ACM Transactions on Graphics (Proc. ACM SIGGRAPH 2009). PDF video |
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Modeling from Contour Drawings Vladislav Kraevoy, Alla Sheffer, Michiel van de Panne Eurographics/ACM Symposium on Sketch-Based Interfaces and Modeling 2009 PDF (10 Mb) video MOV (135 Mb) |
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Single Photo Estimation of Hair Appearance Nicolas Bonneel, Sylvain Paris, Michiel van de Panne, Fredo Durand, George Drettakis Computer Graphics Forum (Proc. Eurographics Symposium on Rendering 2009) PDF video |
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2008 |
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Reusable Skinning Templates Using Cage-based Deformations Tao Ju, Qian-Yi Zhou, Michiel van de Panne, Danny Cohen-Or, Ulrich Neumann ACM Transactions on Graphics (Proc. ACM SIGGRAPH ASIA 2008). PDF (10 pages, 9.3 Mb) video |
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Synthesis of Constrained Walking Skills Stelian Coros, Philippe Beaudoin, KangKang Yin, and Michiel van de Panne. ACM Transactions on Graphics (Proc. ACM SIGGRAPH ASIA 2008). project page |
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Continuation Methods for Adapting Simulated Skills KangKang Yin, Stelian Coros, Philippe Beaudoin, Michiel van de Panne ACM Transactions on Graphics (Proc. ACM SIGGRAPH 2008) project page PDF (7 pages, 3.2 Mb) video (37 Mb) |
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Motion-Motif Graphs. Philippe Beaudoin, Michiel van de Panne, Pierre Poulin and Stelian Coros. ACM/EG Symposium on Computer Animation 2008. PDF (10 pages, 1.3 MB) video (30 MB) PDF of Large Graph (200 Kb) 2007 tech report PDF (11 pages, 1.9 MB) 2007 tech report AVI (42 MB) |
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2007 |
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SIMBICON: Simple Biped Locomotion Control KangKang Yin, Kevin Loken, and Michiel van de Panne ACM Transactions on Graphics (Proc. ACM SIGGRAPH 2007) project page PDF (10 pages, 0.8 Mb) JSIMBICON Java Applet videos: overview drunk walk hill slip box trip spin walk high-to-low gravity hills limping |
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Adapting Wavelet Compression to Human Motion Capture Clips Philippe Beaudoin, Pierre Poulin, and Michiel van de Panne. Graphics Interface 2007 PDF (6 pages, 0.8 MB) video (AVI, 37 MB) |
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Faster Motion Planning Using Learned Local Viability Models Maciej Kalisiak and Michiel van de Panne. ICRA 2007: IEEE International Conference on Robotics and Automation project page PDF (6 pages, 1 Mb) |
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2006 |
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Constellation Models for Sketch Recognition Dana Sharon and Michiel van de Panne. Eurographics Workshop on Sketch Based Interfaces and Modeling 2006 PDF (8 pages, 1.6 Mb) |
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"Walk to here": A Voice-Driven Animation System Zhijin Wang and Michiel van de Panne. SCA 2006: SIGGRAPH/EG Symposium on Computer Animation PDF (9 pages, 4.3 Mb) video (AVI, 50 Mb) |
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Slow-in and Slow-out Cartoon Animation Filter David White, Kevin Loken, and Michiel van de Panne. Poster, ACM SIGGRAPH 2006 PDF (1 pages, 0.2 Mb) video (MOV, 18 MB) |
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RRT-blossom: RRT with a local flood-fill behavior Maciej Kalisiak and Michiel van de Panne. ICRA 2006: IEEE International Conference on Robotics and Automation PDF (7 pages, 0.5 Mb) project page |
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2005 |
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Data-driven Interactive Balancing Behaviors Motion capture data is kinematic in nature. How can we build models of motions that allow us to interact with characters using forces? This work applies a data-driven approach to computing appropriate responses for a character that is being pushed.
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Sketch-based Modeling of Parameterized Objects Sketch-based modeling holds the promise of making 3D modeling accessible to a signicantly wider audience than current modeling tools. We present a modeling system that is capable of constructing 3D models of particular object classes from 2D sketches. The core of the system is a sketch recognition algorithm that seeks to match the points and curves of a set of given 2D templates to the sketch. The system builds models of cups and mugs, airplanes, and fish from sketches.
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Learning Steering Behaviours
Many planning algorithms for steering assume the existence of a complete model of the world. In this project, we construct reactive steering behaviours which use only a simple set of four distance measurements in order to guide the steering. We construct reactive policies for steering cars and trucks-with-trailer forwards and backwards through constrained winding tracks.
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Learning to Control Physics-based Stylized Walking
Successful walking requires the careful control of balance throughout the motion. Developing feedback-based control strategies for physics-based walking simulations is surprisingly difficult. Given a key-framed animation that describes a desired style of walk, we learn a control policy that satisfies the competing goals of both imitating the desired style and maintaining balance.
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Interactive Control of Physics-based 3D Characters
A major challenge in creating physics-based animation is that of solving for the required control to achieve desired behaviours, especially for complex models such as humans and many animals. We propose two interfaces which let a user or game-player interactively control the motions of 3D multi-link rigid body simulations of aerial motions such as diving, ski jumping, and snowboarding.
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Motion Doodles: An Interface for Sketching Character Motion
Matthew Thorne, David Burke, and Michiel van de Panne, ACM Transactions on Graphics, 23(3), Proceedings of SIGGRAPH 2004. project page |
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Motion Perception
The human visual system is not a camera, which creates the potential to manipulate images and animations in convenient, imperceptible ways. Examples of this include the representation of colour (using RGB instead of a spectral distribution) and the choice of frame-rate for displaying animations. In this project we ask other basic questions such as "To what extent can one change the length of objects during an animated motion without this being observed? How does the user's attention affect this result?".
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Isosurface Visualization Using the Contour Tree
The contour tree is an abstraction that encodes the nesting relationships of isosurfaces. It can be used to accelerate isosurface extraction, to identify important isovalues for volume rendering transfer functions, and to guide exploratory visualization through a flexible isosurface interface.
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Computing Viability Envelopes
The viability envelope consists of all points of no return where a system will inevitably succumb to failure, such as a car heading towards a wall or obstacle. We present a method for computing an explicit model of the viability envelope and using this to automatically constrain a users steering behaviour to that which allows maximum freedom while guaranteeing that failure cannot occur.
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2003 |
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Ski Stunt Simulator project web page and download This project implements a realistic planar simulation of the physics involved in performing acrobatic ski stunts. The pose of the skier can be interactively controlled with the mouse. Thus performing any given stunt requires the right combination of both physics and skill, as in real life. A large variety of stunts can be performed, including anything ranging from a triple back flip to a triple front flip. The resulting simulator can be viewed as a game, a teaching tool for kinesiology, or as a preliminary sports prototyping tool.
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2002Was on leave July 2000 - July 2001. |
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Stable Algorithms for Animating Shallow Water Waves project web page Building on previous work in fluid mechanics, we are developing an efficient, stable shallow-water model appropriate for use in computer graphics.
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2001 |
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Composable controllers for physics-based character animations An ambitious goal in the area of physics-based computer animation is the creation of virtual actors that autonomously synthesize realistic human motions and possess a broad repertoire of lifelike motor skills. However, designing the controllers that encompass everyday skills such as walking, running, and getting up from a chair is a very daunting task. This project proposes a framework for composing specialist controllers, possibly designed by different researchers, into more general composite controllers having broader functionality.
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2000 |
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Grasp-based Human Motion Planning The automated animation of human characters continues to be a challenge in computer graphics. We present a novel kinematic motion planning algorithm for character animation which addresses some of the outstanding problems. The problem domain for our algorithm is as follows: given an environment with designated handholds and footholds, determine the motion as an optimization problem. The algorithm exploits a combination of geometric constraints, posture heuristics, and gradient descent optimization in order to arrive at an appropriate motion sequence.
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Interactive Control for Physically-based Animation
project web page
Much as humans and animals control their motions with commands to their muscles, this project examines the feasibility of having an animator control the motion of a simulated character through commands to the character's virtual musculature. Such interfaces are intended to exploit human skill and intuition about the physics of motion in order to create equally skillful animated characters.
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Overview Papers |
Overview Papers
The following papers are for the most part a synthesis of a number of previously published results.
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1999 |
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Efficient Compression Techniques for Precomputed Visibility In rendering large models, it is important to efficiently identify the small subset of primitives that is visible from a given viewpoint. One approach is to partition the viewpoint space into viewpoint cells, and then precompute a visibility table which explicitly records for each viewpoint cell whether or not each each primitive is potentially visible. We propose two algorithms for compressing such visibility tables in order to produce compact and natural descriptions of potentially-visible sets. Alternatively, the algorithms can be thought of as techniques for clustering cells and clustering primitives according to their visibility criteria.
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Invited Talk |
Invited Talk
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1998 |
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Shape Modeling of the Human Arm project web page Generating realistic skin deformations arising from joint movement and muscle contraction is a requirement for producing realistic human character animation. We exploit range image technology to capture the human form and create parameterized animated surface models based upon this data. The work improves in several ways upon algorithms required to process and integrate the range data, as well as parameterizing the surface. Results are presented for the parameterized flexion of a human arm model.
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Footprint-based Quadruped Motion Synthesis
This paper applies trajectory-based optimization techniques to the synthesis of quadruped motions. The animator specifies hard constraints, consisting of footprint locations and their timings, and soft constraints that encode both physically-plausible behavior and the notion of comfortable positions. By dealing first and foremost with the spline trajectories representing the gross motion of the quadruped, the resulting optimization problem can be solved efficiently and robustly. Results include walking, jumping, and galloping quadrupeds.
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Rendering Generalized Cylinders with Paintstrokes
We use semi-transparent generalized cylinders to efficiently approximate the appearance of fine-scale geometry such as fur and pine needles on a branch. We present an efficient technique for dynamically tessellating generalized cylinders. We make direct use of the generalized cylinder's screen-space projection in order to minimize the number of polygons required to construct its image. Used in conjunction with our A-buffer polygon renderer, our technique strikes a good balance between speed and image quality when used at small to medium scales, generally surpassing other methods for rendering generalized cylinders.
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1997 |
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EG Workshop on Computer Animation and Simulation '97
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From Footprints to Animation
We present a method of synthesizing walking, leaping, and running motions for bipeds from a set of input footprints and timing information.
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Dynamic Animation Synthesis with Free-Form Deformations
Free-form deformations (FFDs) have long been a popular tool in modeling and keyframe animation. This paper extends the use of FFDs to a dynamic setting. A goal of this work is to enable normally rigid objects, such as teapots and tables, to come alive and learn to move about. Objects are assigned mass distributions and deformation properties, which allows them to translate, rotate, and deform according to internal and external forces.
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Monaco, February 19-21, 1997, Monaco, 231-241. European Control Conference, July 1-4, 1997, Brussels, 191-210. 1996 | ||||
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Limit Cycle Control of Walking Seemingly simple behaviours such as human walking are difficult to model because of their inherent instability. This research proposes an approach to generating balanced 3D walking motions for physically-based computer animations by viewing the motions as a sequence of discrete cycles in state space. First, a mechanism to stabilize open loop walking motions is presented. Once this basic "balance" mechanism is in place, the underlying open loop motion can then be modified to generate variations on the basic walking gait.
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Motion Synthesis by Example A technique is proposed for creating new animation from a set of representative example motions stored in a motion database. Animations are created by cutting-and-pasting together the example motion segments as required. Motion segments are selected based upon how well they fit into a desired motion and are then automatically tailored for a precise fit. Various fundamental problems associated with the use of motion databases are outlined. A prototype implementation is used to validate the proposed concepts and to explore possible solutions to the aforementioned problems.
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A Planning Algorithm for Dynamic Motions A technique is proposed for creating new animation from a set of representative example motions stored in a motion database. Animations are created by cutting-and-pasting together the example motion segments as required. Motion segments are selected based upon how well they fit into a desired motion and are then automatically tailored for a precise fit. Various fundamental problems associated with the use of motion databases are outlined. A prototype implementation is used to validate the proposed concepts and to explore possible solutions to the aforementioned problems.
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Parameterized Gait Synthesis We present a technique to produce a variety of physics-based gaits by using parameterized finite-state machine controllers that drive a motion in a way analogous to that of a windup-toy. Forward-dynamics simulation produces the final animation. We demonstrate results on creatures having two, four, and six legs.
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1995 | ||||
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Guided Optimization for Balanced Locomotion We present a continuation-method that uses a "hand of god" in order to support a walking biped during learning. As the learned control improves, the external forces applied by the "hand of god" are gradually diminished.
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1994 | ||||
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Synthesizing Parameterized Motions In striving to construct higher level control representations for simulated characters or creatures, one must seek flexible control representations to build upon. We present a method for the synthesis of parameterized, physics-based motions. The basis of the method is a low-level control representation in which linear combinations of controllers generally produce predictable in-between motions.
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Virtual Windup Toys
We propose a new method of automatically finding periodic modes of locomotion for arbitrary articulated figures. Cyclic pose control graphs are used as our control representation. These specifically constrain the controller synthesis process to only those controllers producing periodic driving functions.
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Control Techniques for Physically-Based Animation
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1993 |
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Sensor Actuator Networks Sensor-actuator networks (SANs) are a new approach for the physically-based animation of objects. The user supplies the configuratíon of a mechanical system that has been augmented with simple sensors and actuators. It is then possible to automatically discover many possible modes of locomotion for the given object. The SANs providing the control for these modes of locomotion are simple in structure and produce robust control. A SAN consists of a small non-linear network of weighted connections between sensors and actuators. A stochastic procedure for finding and then improving suitable SANs is given. Ten different creatures controlled by this method are presented.
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Physically-based modeling and control of turning
We present a method for planning turning motions for an inverted pendulum model. We demonstrate its use to plan realistic turning behaviors, using bicyclists, skiers, and snowboarders as examples.
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Optimal Controller Synthesis Using Approximating-Graph Dynamic Programming
Dynamic programming is performed for continuous-state problems by developing an appropriate discretization technique. We demonstrate results on systems having up to a 5-dimensional state space.
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1992 | ||||
A Controller for the Dynamic Walk of a Biped Across Variable Terrain We develop a control strategy for controlling the simulated walk of a 7-link planar biped using dynamic programming as the core control mechanims.
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Control Techniques for Physically- Based Animation,
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1991 | ||||
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1990 | ||||
Reusable Motion Synthesis Using State-Space Controllers We apply dynamic programming to continuous state space to approximate optimal controllers for several low-dimensional systems. Animated motion can then be created by applying the controllers to the dynamical systems and observing the evolution of the state over time.
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1989
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