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Wenping Wang

5 papers here

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

author position
  • middle author3
  • last author2

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

fields
  • cs.CV4
  • cs.RO1
same name
  • Wenping Wang — 21 papers, h 32
  • Wenping Wang — 16 papers, h 12
  • Wenping Wang — 14 papers
  • Wenping Wang — 14 papers
  • Wenping Wang — 13 papers, h 10
  • Wenping Wang — 13 papers, h 3

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

most citedWonder3D: Single Image to 3D using Cross-Domain Diffusion

25 citations · 48 across the 3 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024★ 21 cited

GaussianPro: 3D Gaussian Splatting with Progressive Propagation

Kai Cheng, Xiaoxiao Long, Kaizhi Yang +5

The advent of 3D Gaussian Splatting (3DGS) has recently brought about a revolution in the field of neural rendering, facilitating high-quality renderings at real-time speed. Howeve…

cs.CV2023

GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfaces

Yingwenqi Jiang, Jiadong Tu, Yuan Liu +4

The advent of neural 3D Gaussians has recently brought about a revolution in the field of neural rendering, facilitating the generation of high-quality renderings at real-time spee…

cs.CV2023★ 25 cited

Wonder3D: Single Image to 3D using Cross-Domain Diffusion

Xiaoxiao Long, Yuan-Chen Guo, Cheng Lin +8

In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images.Recent methods based on Score Distillation Samp…

cs.CV2023★ 2 cited

Model2Scene: Learning 3D Scene Representation via Contrastive Language-CAD Models Pre-training

Runnan Chen, Xinge Zhu, Nenglun Chen +6

Current successful methods of 3D scene perception rely on the large-scale annotated point cloud, which is tedious and expensive to acquire. In this paper, we propose Model2Scene, a…

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