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Bo Pang

5 papers hereh-index 327 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2
  • last author1

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.GR1
same name
  • Bo Pang — 14 papers, h 29
  • Bo Pang — 13 papers, h 15
  • Bo Pang — 13 papers, h 5
  • Bo Pang — 7 papers, h 5
  • Bo Pang — 6 papers, h 10
  • Bo Pang — 6 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedLearning the Geodesic Embedding with Graph Neural Networks

8 citations · 8 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

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.CV2024

Joint Point Cloud Upsampling and Cleaning with Octree-based CNNs

Jihe Li, Bo Pang, Peng-Shuai Wang

Recovering dense and uniformly distributed point clouds from sparse or noisy data remains a significant challenge. Recently, great progress has been made on these tasks, but usuall…

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.