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Lei Luo

13 papers hereh-index 7242 citations34 works total

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

author position
  • sole author1
  • first author2
  • middle author5
  • last author5

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV10
  • cs.LG2
  • math.FA1
same name
  • Lei Luo — 5 papers, h 3
  • Lei Luo — 5 papers, h 2
  • Lei Luo — 5 papers, h 3
  • Lei Luo — 3 papers, h 2
  • Lei Luo — 3 papers, h 17
  • Lei Luo — 2 papers, h 7

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
20232026
most citedFrequency-Spatial Entanglement Learning for Camouflaged Object Detection

5 citations · 8 across the 12 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CV2024

United Domain Cognition Network for Salient Object Detection in Optical Remote Sensing Images

Yanguang Sun, Jian Yang, Lei Luo

Recently, deep learning-based salient object detection (SOD) in optical remote sensing images (ORSIs) have achieved significant breakthroughs. We observe that existing ORSIs-SOD me…

cs.CV2024★ 3 cited

GLCONet: Learning Multi-source Perception Representation for Camouflaged Object Detection

Yanguang Sun, Hanyu Xuan, Jian Yang +1

Recently, biological perception has been a powerful tool for handling the camouflaged object detection (COD) task. However, most existing methods are heavily dependent on the local…

cs.CV2024★ 5 cited

Frequency-Spatial Entanglement Learning for Camouflaged Object Detection

Yanguang Sun, Chunyan Xu, Jian Yang +2

Camouflaged object detection has attracted a lot of attention in computer vision. The main challenge lies in the high degree of similarity between camouflaged objects and their sur…

cs.CV2024

Diff-Reg v1: Diffusion Matching Model for Registration Problem

Qianliang Wu, Haobo Jiang, Lei Luo +4

Establishing reliable correspondences is essential for registration tasks such as 3D and 2D3D registration. Existing methods commonly leverage geometric or semantic point features…

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