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Peng Li

5 papers hereh-index 5355 citations17 works total

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

author position
  • middle author5

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

fields
  • cs.CV4
  • cs.LG1
same name
  • Peng Li — 22 papers, h 37
  • Peng Li — 22 papers, h 65
  • Peng Li — 13 papers, h 5
  • Peng Li — 11 papers
  • Peng Li — 10 papers, h 3
  • Peng Li — 9 papers, h 12

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
20222025
most citedGeoGCN: Geometric Dual-domain Graph Convolution Network for Point Cloud Denoising

1 citations · 1 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025

ColorGS: High-fidelity Surgical Scene Reconstruction with Colored Gaussian Splatting

Qun Ji, Peng Li, Mingqiang Wei

High-fidelity reconstruction of deformable tissues from endoscopic videos remains challenging due to the limitations of existing methods in capturing subtle color variations and mo…

cs.CV2025

CoreEditor: Correspondence-constrained Diffusion for Consistent 3D Editing

Zhe Zhu, Honghua Chen, Peng Li +1

Text-driven 3D editing seeks to modify 3D scenes according to textual descriptions, and most existing approaches tackle this by adapting pre-trained 2D image editors to multi-view…

cs.CV2024

PointCG: Self-supervised Point Cloud Learning via Joint Completion and Generation

Yun Liu, Peng Li, Xuefeng Yan +6

The core of self-supervised point cloud learning lies in setting up appropriate pretext tasks, to construct a pre-training framework that enables the encoder to perceive 3D objects…

cs.CV2022★ 1 cited

GeoGCN: Geometric Dual-domain Graph Convolution Network for Point Cloud Denoising

Zhaowei Chen, Peng Li, Zeyong Wei +4

We propose GeoGCN, a novel geometric dual-domain graph convolution network for point cloud denoising (PCD). Beyond the traditional wisdom of PCD, to fully exploit the geometric inf…

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