150 citations · 443 across the 19 of their papers we have counts for
19 papers
Computing Medial Axis Transform with Feature Preservation via Restricted Power Diagram
Ningna Wang, Bin Wang, Wenping Wang +1
We propose a novel framework for computing the medial axis transform of 3D shapes while preserving their medial features via restricted power diagram (RPD). Medial features, includ…
Coverage Axis: Inner Point Selection for 3D Shape Skeletonization
Zhiyang Dou, Cheng Lin, Rui Xu +4
In this paper, we present a simple yet effective formulation called Coverage Axis for 3D shape skeletonization. Inspired by the set cover problem, our key idea is to cover all the…
Unsupervised Shape Completion via Deep Prior in the Neural Tangent Kernel Perspective
Lei Chu, Hao Pan, Wenping Wang
We present a novel approach for completing and reconstructing 3D shapes from incomplete scanned data by using deep neural networks. Rather than being trained on supervised completi…
SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform
Cheng Lin, Lingjie Liu, Changjian Li +4
Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications. Exis…
Modeling 3D Shapes by Reinforcement Learning
Cheng Lin, Tingxiang Fan, Wenping Wang +1
We explore how to enable machines to model 3D shapes like human modelers using deep reinforcement learning (RL). In 3D modeling software like Maya, a modeler usually creates a mesh…
Top-Down Shape Abstraction Based on Greedy Pole Selection
Zhiyang Dou, Shiqing Xin, Rui Xu +6
Motivated by the fact that the medial axis transform is able to encode nearly the complete shape, we propose to use as few medial balls as possible to approximate the original encl…