5 citations · 6 across the 6 of their papers we have counts for
7 papers
KODA: Kinematics--Observation Data Alignment for Humanoid Learning from Human Egocentric Demonstration
Zibo Zhou, Yueru Chen, Junsong Wu +8
Training humanoid whole-body vision-language-action (VLA) policies requires costly robot demonstrations with aligned robot-view observations and controller-compatible whole-body st…
GLoRI: Closed-Loop Whole-Body Tracking with Global-Local Reference Interaction for Humanoid Loco-Manipulation
Qingyao Xu, Sheng Yin, Zibo Zhou +3
Humanoid loco-manipulation requires accurate whole-body motion tracking in the world frame for physical interaction. While local references preserve motion structure, they lack exp…
EmboMatrix: A Scalable Training-Ground for Embodied Decision-Making
Zixing Lei, Sheng Yin, Yichen Xiong +8
Embodied decision-making enables agents to translate high-level goals into executable actions through continuous interactions within the physical world, forming a cornerstone of ge…
PolySim: Bridging the Sim-to-Real Gap for Humanoid Control via Multi-Simulator Dynamics Randomization
Zixing Lei, Zibo Zhou, Sheng Yin +7
Humanoid whole-body control (WBC) policies trained in simulation often suffer from the sim-to-real gap, which fundamentally arises from simulator inductive bias, the inherent assum…
ChatBEV: Empowering Traffic Scene Understanding and Simulation via Vision-Language Model
Qingyao Xu, Ya Zhang, Yanfeng Wang +1
Comprehensive traffic scene understanding is a foundational capability for Intelligent Transportation Systems (ITS) underpinning applications such as traffic simulation. While Visi…
Language-Driven Interactive Traffic Trajectory Generation
Junkai Xia, Chenxin Xu, Qingyao Xu +3
Realistic trajectory generation with natural language control is pivotal for advancing autonomous vehicle technology. However, previous methods focus on individual traffic particip…
Joint-Relation Transformer for Multi-Person Motion Prediction
Qingyao Xu, Weibo Mao, Jingze Gong +5
Multi-person motion prediction is a challenging problem due to the dependency of motion on both individual past movements and interactions with other people. Transformer-based meth…