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U. Neumann

17 papers hereh-index 6515.2k citations299 works total

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

author position
  • middle author2
  • last author15

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

fields
  • cs.CV15
  • cs.GR1
  • eess.IV1
same name
  • U. Neumann — 11 papers, h 16
  • U. Neumann — 1 paper, h 1
  • U. Neumann — 1 paper, h 7
  • U. Neumann — 1 paper, h 6

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
20172023
most citedLearning to Prune Filters in Convolutional Neural Networks

27 citations · 65 across the 10 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019

Grid-GCN for Fast and Scalable Point Cloud Learning

Qiangeng Xu, Xudong Sun, Cho-Ying Wu +2

Due to the sparsity and irregularity of the point cloud data, methods that directly consume points have become popular. Among all point-based models, graph convolutional networks (…

eess.IV2019

Salient Building Outline Enhancement and Extraction Using Iterative L0 Smoothing and Line Enhancing

Cho-Ying Wu, Ulrich Neumann

In this paper, our goal is salient building outline enhancement and extraction from images taken from consumer cameras using L0 smoothing. We address weak outlines and over-smoothi…

cs.CV2019

Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion

Yiqi Zhong, Cho-Ying Wu, Suya You +1

In this paper, we propose our Correlation For Completion Network (CFCNet), an end-to-end deep learning model that uses the correlation between two data sources to perform sparse de…

cs.CV2019★ 10 cited

3DN: 3D Deformation Network

Weiyue Wang, Duygu Ceylan, Radomir Mech +1

Applications in virtual and augmented reality create a demand for rapid creation and easy access to large sets of 3D models. An effective way to address this demand is to edit or d…

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