4 citations · 7 across the 7 of their papers we have counts for
7 papers
DualPrim: Compact 3D Reconstruction with Positive and Negative Primitives
Xiaoxu Meng, Zhongmin Chen, Bo Yang +3
Neural reconstructions often trade structure for fidelity, yielding dense and unstructured meshes with irregular topology and weak part boundaries that hinder editing, animation, a…
PRIMP: PRobabilistically-Informed Motion Primitives for Efficient Affordance Learning from Demonstration
Sipu Ruan, Weixiao Liu, Xiaoli Wang +2
This paper proposes a learning-from-demonstration method using probability densities on the workspaces of robot manipulators. The method, named "PRobabilistically-Informed Motion P…
Learning-Free Grasping of Unknown Objects Using Hidden Superquadrics
Yuwei Wu, Weixiao Liu, Zhiyang Liu +1
Robotic grasping is an essential and fundamental task and has been studied extensively over the past several decades. Traditional work analyzes physical models of the objects and c…
Marching-Primitives: Shape Abstraction from Signed Distance Function
Weixiao Liu, Yuwei Wu, Sipu Ruan +1
Representing complex objects with basic geometric primitives has long been a topic in computer vision. Primitive-based representations have the merits of compactness and computatio…
Primitive-based Shape Abstraction via Nonparametric Bayesian Inference
Yuwei Wu, Weixiao Liu, Sipu Ruan +1
3D shape abstraction has drawn great interest over the years. Apart from low-level representations such as meshes and voxels, researchers also seek to semantically abstract complex…
Robust and Accurate Superquadric Recovery: a Probabilistic Approach
Weixiao Liu, Yuwei Wu, Sipu Ruan +1
Interpreting objects with basic geometric primitives has long been studied in computer vision. Among geometric primitives, superquadrics are well known for their ability to represe…
LSG-CPD: Coherent Point Drift with Local Surface Geometry for Point Cloud Registration
Weixiao Liu, Hongtao Wu, Gregory Chirikjian
Probabilistic point cloud registration methods are becoming more popular because of their robustness. However, unlike point-to-plane variants of iterative closest point (ICP) which…