13 citations · 25 across the 14 of their papers we have counts for
15 papers
IMR: Iterative Mode-World Weighted Regression for Multi-Agent Trajectory Prediction
Honglin Wang, Shiyao Pan, Yun-Fu Liu
Multi-agent motion prediction is essential for automated vehicles to understand the intentions of surrounding vehicles. However, previous prediction-based and anchor-based methods…
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
Learning Athletic Humanoid Tennis Skills from Imperfect Human Motion Data
Zhikai Zhang, Haofei Lu, Yunrui Lian +12
Human athletes demonstrate versatile and highly-dynamic tennis skills to successfully conduct competitive rallies with a high-speed tennis ball. However, reproducing such behaviors…
Collision-Free Humanoid Traversal in Cluttered Indoor Scenes
Han Xue, Sikai Liang, Zhikai Zhang +7
We study the problem of collision-free humanoid traversal in cluttered indoor scenes, such as hurdling over objects scattered on the floor, crouching under low-hanging obstacles, o…
Unleashing Humanoid Reaching Potential via Real-world-Ready Skill Space
Zhikai Zhang, Chao Chen, Han Xue +6
Humans possess a large reachable space in the 3D world, enabling interaction with objects at varying heights and distances. However, realizing such large-space reaching on humanoid…
Mimicking-Bench: A Benchmark for Generalizable Humanoid-Scene Interaction Learning via Human Mimicking
Yun Liu, Bowen Yang, Licheng Zhong +2
Learning generic skills for humanoid robots interacting with 3D scenes by mimicking human data is a key research challenge with significant implications for robotics and real-world…
ManiVideo: Generating Hand-Object Manipulation Video with Dexterous and Generalizable Grasping
Youxin Pang, Ruizhi Shao, Jiajun Zhang +5
In this paper, we introduce ManiVideo, a novel method for generating consistent and temporally coherent bimanual hand-object manipulation videos from given motion sequences of hand…
SyncDiff: Synchronized Motion Diffusion for Multi-Body Human-Object Interaction Synthesis
Wenkun He, Yun Liu, Ruitao Liu +1
Synthesizing realistic human-object interaction motions is a critical problem in VR/AR and human animation. Unlike the commonly studied scenarios involving a single human or hand i…
CORE4D: A 4D Human-Object-Human Interaction Dataset for Collaborative Object REarrangement
Yun Liu, Chengwen Zhang, Ruofan Xing +3
Understanding how humans cooperatively rearrange household objects is critical for VR/AR and human-robot interaction. However, in-depth studies on modeling these behaviors are unde…
TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understanding
Yun Liu, Haolin Yang, Xu Si +5
Humans commonly work with multiple objects in daily life and can intuitively transfer manipulation skills to novel objects by understanding object functional regularities. However,…
Curricular Subgoals for Inverse Reinforcement Learning
Shunyu Liu, Yunpeng Qing, Shuqi Xu +6
Inverse Reinforcement Learning (IRL) aims to reconstruct the reward function from expert demonstrations to facilitate policy learning, and has demonstrated its remarkable success i…
UniDexGrasp++: Improving Dexterous Grasping Policy Learning via Geometry-aware Curriculum and Iterative Generalist-Specialist Learning
Weikang Wan, Haoran Geng, Yun Liu +4
We propose a novel, object-agnostic method for learning a universal policy for dexterous object grasping from realistic point cloud observations and proprioceptive information unde…
CAMS: CAnonicalized Manipulation Spaces for Category-Level Functional Hand-Object Manipulation Synthesis
Juntian Zheng, Qingyuan Zheng, Lixing Fang +2
In this work, we focus on a novel task of category-level functional hand-object manipulation synthesis covering both rigid and articulated object categories. Given an object geomet…
Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing
Yun Liu, Xiaomeng Xu, Weihang Chen +5
When manipulating an object to accomplish complex tasks, humans rely on both vision and touch to keep track of the object's 6D pose. However, most existing object pose tracking sys…
HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object Interaction
Yunze Liu, Yun Liu, Che Jiang +7
We present HOI4D, a large-scale 4D egocentric dataset with rich annotations, to catalyze the research of category-level human-object interaction. HOI4D consists of 2.4M RGB-D egoce…