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researcher

Na Lei

19 papers hereh-index 191.5k citations89 works total

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

author position
  • first author6
  • middle author11

Across the 17 of 19 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • cs.CG4
  • cs.CV4
  • cs.GR4
  • cs.AI1
  • cs.RO1
same name
  • Na Lei — 12 papers, h 4
  • Na Lei — 4 papers, h 6
  • Na Lei — 1 paper, h 2
  • Na Lei — 1 paper, h 1
  • Na Lei — 1 paper, h 2

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
20172024
most citedGeometric Understanding of Deep Learning

34 citations · 139 across the 19 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

Global Parameterization-based Texture Space Optimization

Wei Chen, Yuxue Ren, Na Lei +2

Texture mapping is a common technology in the area of computer graphics, it maps the 3D surface space onto the 2D texture space. However, the loose texture space will reduce the ef…

cs.CV2022

Global Consistent Point Cloud Registration Based on Lie-algebraic Cohomology

Yuxue Ren, Baowei Jiang, Wei Chen +2

We present a novel, effective method for global point cloud registration problems by geometric topology. Based on many point cloud pairwise registration methods (e.g ICP), we focus…

cs.CV2020

Ricci Curvature Based Volumetric Segmentation of the Auditory Ossicles

Na Lei, Jisui Huang, Yuxue Ren +2

The auditory ossicles that are located in the middle ear are the smallest bones in the human body. Their damage will result in hearing loss. It is therefore important to be able to…

cs.CV2020★ 1 cited

AE-OT-GAN: Training GANs from data specific latent distribution

Dongsheng An, Yang Guo, Min Zhang +4

Though generative adversarial networks (GANs) areprominent models to generate realistic and crisp images,they often encounter the mode collapse problems and arehard to train, which…

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