29 citations · 34 across the 11 of their papers we have counts for
12 papers
Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
Junli Wang, Zhihua Hua, Xueyi Liu +7
Existing imitation learning methods for end-to-end autonomous driving predominantly learn from successful demonstrations by minimizing geometric deviations from expert trajectories…
DexNDM: Closing the Reality Gap for Dexterous In-Hand Rotation via Joint-Wise Neural Dynamics Model
Xueyi Liu, He Wang, Li Yi
Achieving generalized in-hand object rotation remains a significant challenge in robotics, largely due to the difficulty of transferring policies from simulation to the real world.…
DexTrack: Towards Generalizable Neural Tracking Control for Dexterous Manipulation from Human References
Xueyi Liu, Jianibieke Adalibieke, Qianwei Han +2
We address the challenge of developing a generalizable neural tracking controller for dexterous manipulation from human references. This controller aims to manage a dexterous robot…
MobileH2R: Learning Generalizable Human to Mobile Robot Handover Exclusively from Scalable and Diverse Synthetic Data
Zifan Wang, Ziqing Chen, Junyu Chen +6
This paper introduces MobileH2R, a framework for learning generalizable vision-based human-to-mobile-robot (H2MR) handover skills. Unlike traditional fixed-base handovers, this tas…
QuasiSim: Parameterized Quasi-Physical Simulators for Dexterous Manipulations Transfer
Xueyi Liu, Kangbo Lyu, Jieqiong Zhang +2
We explore the dexterous manipulation transfer problem by designing simulators. The task wishes to transfer human manipulations to dexterous robot hand simulations and is inherentl…
GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion
Xueyi Liu, Li Yi
In this work, we tackle the challenging problem of denoising hand-object interactions (HOI). Given an erroneous interaction sequence, the objective is to refine the incorrect hand…
Few-Shot Physically-Aware Articulated Mesh Generation via Hierarchical Deformation
Xueyi Liu, Bin Wang, He Wang +1
We study the problem of few-shot physically-aware articulated mesh generation. By observing an articulated object dataset containing only a few examples, we wish to learn a model t…
Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance
Xueyi Liu, Ji Zhang, Ruizhen Hu +3
Category-level articulated object pose estimation aims to estimate a hierarchy of articulation-aware object poses of an unseen articulated object from a known category. To reduce t…
Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training
Xueyi Liu, Yu Rong, Tingyang Xu +3
Graph instance contrastive learning has been proved as an effective task for Graph Neural Network (GNN) pre-training. However, one key issue may seriously impede the representative…
AutoGPart: Intermediate Supervision Search for Generalizable 3D Part Segmentation
Xueyi Liu, Xiaomeng Xu, Anyi Rao +2
Training a generalizable 3D part segmentation network is quite challenging but of great importance in real-world applications. To tackle this problem, some works design task-specif…
Network representation learning: A macro and micro view
Xueyi Liu, Jie Tang
Graph is a universe data structure that is widely used to organize data in real-world. Various real-word networks like the transportation network, social and academic network can b…
Understanding WeChat User Preferences and "Wow" Diffusion
Fanjin Zhang, Jie Tang, Xueyi Liu +9
WeChat is the largest social instant messaging platform in China, with 1.1 billion monthly active users. "Top Stories" is a novel friend-enhanced recommendation engine in WeChat, i…