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Ningna Wang

11 papers hereh-index 480 citations13 works total

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

author position
  • first author4
  • middle author7

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.GR6
  • cs.CV4
  • cs.RO1
same name
  • Ningna Wang — 2 papers, h 5

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
20242026
most citedMATStruct: High-Quality Medial Mesh Computation via Structure-aware Variational Optimization

2 citations · 4 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

MVFusion-GS: Motion-Variance Guided Temporal Attention for High-Quality Dynamic Gaussian Splatting

Jianwei Hu, Tingxuan Huang, Hengyu Zhou +4

3D Gaussian Splatting (3DGS) enables real-time novel view synthesis for static scenes. Extending it to dynamic scenes via deformation fields has recently attracted significant atte…

cs.CV2025★ 1 cited

CADDreamer: CAD Object Generation from Single-view Images

Yuan Li, Cheng Lin, Yuan Liu +6

Diffusion-based 3D generation has made remarkable progress in recent years. However, existing 3D generative models often produce overly dense and unstructured meshes, which stand i…

cs.CV2025

TexHOI: Reconstructing Textures of 3D Unknown Objects in Monocular Hand-Object Interaction Scenes

Alakh Aggarwal, Ningna Wang, Xiaohu Guo

Reconstructing 3D models of dynamic, real-world objects with high-fidelity textures from monocular frame sequences has been a challenging problem in recent years. This difficulty s…

cs.CV2024

NASM: Neural Anisotropic Surface Meshing

Hongbo Li, Haikuan Zhu, Sikai Zhong +7

This paper introduces a new learning-based method, NASM, for anisotropic surface meshing. Our key idea is to propose a graph neural network to embed an input mesh into a high-dimen…

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