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researcher

Ke Wang

4 papers here

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
ORCID 0009-0008-5453-5197
same name
  • Ke Wang — 52 papers, h 28
  • Ke Wang — 11 papers, h 13
  • Ke Wang — 10 papers, h 17
  • Ke Wang — 8 papers, h 46
  • Ke Wang — 8 papers, h 7
  • Ke Wang — 8 papers

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 citedSemi-supervised Parametric Real-world Image Harmonization

3 citations · 7 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

Curricular Object Manipulation in LiDAR-based Object Detection

Ziyue Zhu, Qiang Meng, Xiao Wang +3

This paper explores the potential of curriculum learning in LiDAR-based 3D object detection by proposing a curricular object manipulation (COM) framework. The framework embeds the…

cs.CV2023★ 1 cited

Augment and Criticize: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection

Zhenyu Li, Zhipeng Zhang, Heng Fan +4

In this paper, we improve the challenging monocular 3D object detection problem with a general semi-supervised framework. Specifically, having observed that the bottleneck of this…

cs.CV2023★ 3 cited

Semi-supervised Parametric Real-world Image Harmonization

Ke Wang, Michaël Gharbi, He Zhang +2

Learning-based image harmonization techniques are usually trained to undo synthetic random global transformations applied to a masked foreground in a single ground truth photo. Thi…

cs.CV2023★ 3 cited

DeepMatcher: A Deep Transformer-based Network for Robust and Accurate Local Feature Matching

Tao Xie, Kun Dai, Ke Wang +2

Local feature matching between images remains a challenging task, especially in the presence of significant appearance variations, e.g., extreme viewpoint changes. In this work, we…

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