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We present Diffuse-CLoC, a guided diffusion framework for physics-based look-ahead control that enables intuitive, steerable, and physically realistic motion generation.
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models
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Jonathan Tseng, Rodrigo Castellon, and Karen Liu. 2023 · 2023
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Hierarchical Planning and Control for Box Loco-Manipulation
Zhaoming Xie, Jonathan Tseng, Sebastian Starke, Michiel van de Panne, and C. Karen Liu. 2023 · 2023
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Learning to Transfer In-Hand Manipulations Using a Greedy Shape Curriculum. In Computer graphics forum , Vol. 42. Wiley Online Library, 25–36
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Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
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Neural Categorical Priors for Physics-Based Character Control
Qingxu Zhu, He Zhang, Mengting Lan, and Lei Han. 2023 · 2023
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Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion
Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, and Vincent Sitzmann. 2024 · 2024
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Robot Motion Diffusion Model: Motion Generation for Robotic Characters. In SIGGRAPH Asia 2024 Conference Papers (SA ’24) . Association for Computing Machinery, New York, NY, USA, Article 50, 9 pages
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Agon Serifi, Ruben Grandia, Espen Knoop, Markus Gross, and Moritz Bächer. 2024b · 2024
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Interactive Character Control with Auto-Regressive Motion Diffusion Models
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CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control
Guy Tevet, Sigal Raab, Setareh Cohan, Daniele Reda, Zhengyi Luo, Xue Bin Peng, Amit H. Bermano, and Michiel van de Panne. 2024 · 2024
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One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation
Zhendong Wang, Zhaoshuo Li, Ajay Mandlekar, Zhenjia Xu, Jiaojiao Fan, Yashraj Narang, Linxi Fan, Yuke Zhu, Yogesh Balaji, Mingyuan Zhou, Ming-Yu Liu, and Yu Zeng. 2024 · 2024
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MoConVQ: Unified Physics-Based Motion Control via Scalable Discrete Representations
Heyuan Yao, Zhenhua Song, Yuyang Zhou, Tenglong Ao, Baoquan Chen, and Libin Liu. 2024 · 2024
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TEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis. In ACM SIGGRAPH 2024 Conference Papers (Denver, CO, USA) (SIGGRAPH ’24) . Association for Computing Machinery, New York, NY, USA, Article 68, 11 pages
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