activity
20232026
most citedLearning the Geodesic Embedding with Graph Neural Networks

8 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

CVT-GS: Learning to Simplify 3D Gaussian Splatting with Centroidal Voronoi Tessellation

Bingxian Li, Yilong Li, Jingliang Peng +6

While 3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time novel view synthesis, rendering high-fidelity scenes often relies on a massive number of G…

cs.GR2026

Neural Centroidal Voronoi Tessellations

Jiacheng Xu, Bo Pang, Rui Xu +5

Centroidal Voronoi tessellation (CVT) is a fundamental primitive for high-quality surface sampling and isotropic remeshing in computer graphics. However, computing surface CVTs wit…

cs.CV2026

ViSculpt: Visual-Centric Agentic Geometry Editing

Bo Pang, Jiaqi Pan, Xiaocheng Zhang +3

3D geometry editing is a critical yet labor-intensive part of the graphics pipeline, requiring artists to translate creative intent into precise operations in complex professional…

cs.CV2024

Neural Laplacian Operator for 3D Point Clouds

Bo Pang, Zhongtian Zheng, Yilong Li +2

The discrete Laplacian operator holds a crucial role in 3D geometry processing, yet it is still challenging to define it on point clouds. Previous works mainly focused on construct…

cs.CV2023★ 8 cited

Learning the Geodesic Embedding with Graph Neural Networks

Bo Pang, Zhongtian Zheng, Guoping Wang +1

We present GeGnn, a learning-based method for computing the approximate geodesic distance between two arbitrary points on discrete polyhedra surfaces with constant time complexity…

cs.GR2023

Visual-Guided Mesh Repair

Zhongtian Zheng, Xifeng Gao, Zherong Pan +4

Mesh repair is a long-standing challenge in computer graphics and related fields. Converting defective meshes into watertight manifold meshes can greatly benefit downstream applica…