34 citations · 165 across the 20 of their papers we have counts for
21 papers
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…
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…
UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy
Yinzhen Xu, Weikang Wan, Jialiang Zhang +10
In this work, we tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting. The goal is to grasp and lift up obje…
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…
Complete-to-Partial 4D Distillation for Self-Supervised Point Cloud Sequence Representation Learning
Zhuoyang Zhang, Yuhao Dong, Yunze Liu +1
Recent work on 4D point cloud sequences has attracted a lot of attention. However, obtaining exhaustively labeled 4D datasets is often very expensive and laborious, so it is especi…
GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts
Haoran Geng, Helin Xu, Chengyang Zhao +4
For years, researchers have been devoted to generalizable object perception and manipulation, where cross-category generalizability is highly desired yet underexplored. In this wor…