activity
20192026
most citedNerVE: Neural Volumetric Edges for Parametric Curve Extraction from Point Cloud

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.GR2026

TopGen: Learning Structural Layouts and Cross-Fields for Quadrilateral Mesh Generation

Yuguang Chen, Xinhai Liu, Xiangyu Zhu +4

High-quality quadrilateral mesh generation is a fundamental challenge in computer graphics. Traditional optimization-based methods are often constrained by the topological quality…

cs.CV2024

Controllable Shape Modeling with Neural Generalized Cylinder

Xiangyu Zhu, Zhiqin Chen, Ruizhen Hu +1

Neural shape representation, such as neural signed distance field (NSDF), becomes more and more popular in shape modeling as its ability to deal with complex topology and arbitrary…

cs.CV2023

3D Keypoint Estimation Using Implicit Representation Learning

Xiangyu Zhu, Dong Du, Haibin Huang +2

In this paper, we tackle the challenging problem of 3D keypoint estimation of general objects using a novel implicit representation. Previous works have demonstrated promising resu…

cs.CV2023★ 3 cited

NerVE: Neural Volumetric Edges for Parametric Curve Extraction from Point Cloud

Xiangyu Zhu, Dong Du, Weikai Chen +3

Extracting parametric edge curves from point clouds is a fundamental problem in 3D vision and geometry processing. Existing approaches mainly rely on keypoint detection, a challeng…

cs.CV2019

Two-phase Hair Image Synthesis by Self-Enhancing Generative Model

Haonan Qiu, Chuan Wang, Hang Zhu +3

Generating plausible hair image given limited guidance, such as sparse sketches or low-resolution image, has been made possible with the rise of Generative Adversarial Networks (GA…