24 citations · 67 across the 30 of their papers we have counts for
8 papers · 1 filter
Sample from What You See: Visuomotor Policy Learning via Diffusion Bridge with Observation-Embedded Stochastic Differential Equation
Zhaoyang Liu, Mokai Pan, Zhongyi Wang +5
Imitation learning with diffusion models has advanced robotic control by capturing the multi-modal action distributions. However, existing methods typically treat observations only…
Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios
Yuting Zeng, Zhiwen Zheng, You Zhou +5
This paper proposes a momentum-constrained hybrid heuristic trajectory optimization framework (MHHTOF) tailored for assistive navigation in visually impaired scenarios, integrating…
A Unified and Fast-Sampling Diffusion Bridge Framework via Stochastic Optimal Control
Mokai Pan, Kaizhen Zhu, Yuexin Ma +4
Recent advances in diffusion bridge models leverage Doob's -transform to establish fixed endpoints between distributions, demonstrating promising results in image translation an…
OpenHOI: Open-World Hand-Object Interaction Synthesis with Multimodal Large Language Model
Zhenhao Zhang, Ye Shi, Lingxiao Yang +3
Understanding and synthesizing realistic 3D hand-object interactions (HOI) is critical for applications ranging from immersive AR/VR to dexterous robotics. Existing methods struggl…
DreamPolicy: A Unified World-model Policy for Scalable Humanoid Locomotion
Yahao Fan, Tianxiang Gui, Kaiyang Ji +8
Achieving versatile humanoid locomotion with a single policy presents a critical scalability challenge. Prevailing methods often rely on distilling multiple terrain-specific teache…
GenPO: Generative Diffusion Models Meet On-Policy Reinforcement Learning
Shutong Ding, Ke Hu, Shan Zhong +5
Recent advances in reinforcement learning (RL) have demonstrated the powerful exploration capabilities and multimodality of generative diffusion-based policies. While substantial p…
Human-Object Interaction via Automatically Designed VLM-Guided Motion Policy
Zekai Deng, Ye Shi, Kaiyang Ji +3
Human-object interaction (HOI) synthesis is crucial for applications in animation, simulation, and robotics. However, existing approaches either rely on expensive motion capture da…
ARFlow: Human Action-Reaction Flow Matching with Physical Guidance
Wentao Jiang, Jingya Wang, Kaiyang Ji +3
Human action-reaction synthesis, a fundamental challenge in modeling causal human interactions, plays a critical role in applications ranging from virtual reality to social robotic…