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In this paper, we introduce ControlVAE, a novel model-based framework for learning generative motion control policies based on variational autoencoders (VAE).
When to Trust Your Model: Model-Based Policy Optimization
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Guided Learning of Control Graphs for Physics-Based Characters
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Proximal Policy Optimization Algorithms
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Character Controllers Using Motion VAEs
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On the Variance of the Adaptive Learning Rate and Beyond. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020 . OpenReview.net
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CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotion
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Catch & Carry: Reusable Neural Controllers for Vision-Guided Whole-Body Tasks
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A Scalable Approach to Control Diverse Behaviors for Physically Simulated Characters
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ALLSTEPS: Curriculum-Driven Learning of Stepping Stone Skills. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (Virtual Event, Canada) (SCA ’20) . Eurographics Association, Goslar, DEU, Article 20, 12 pages
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SuperTrack: Motion Tracking for Physically Simulated Characters Using Supervised Learning
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PODS: Policy Optimization via Differentiable Simulation. In International Conference on Machine Learning . PMLR, 7805–7817
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AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control
Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, and Angjoo Kanazawa. 2021 · 2021
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Action-Conditioned 3D Human Motion Synthesis with Transformer VAE. In 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021 . IEEE, 10965–10975
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Neural Animation Layering for Synthesizing Martial Arts Movements
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Fast and feature-complete differentiable physics engine for articulated rigid bodies with contact constraints. In Robotics: Science and Systems
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Discovering Diverse Athletic Jumping Strategies
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GANimator: Neural Motion Synthesis from a Single Sequence
Peizhuo Li, Kfir Aberman, Zihan Zhang, Rana Hanocka, and Olga Sorkine-Hornung. 2022 · 2022
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ASE: Large-Scale Reusable Adversarial Skill Embeddings for Physically Simulated Characters
Xue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine, and Sanja Fidler. 2022 · 2022
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Physics-Based Character Controllers Using Conditional VAEs
Jungdam Won, Deepak Gopinath, and Jessica Hodgins. 2022 · 2022
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