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Hui Lu

4 papers hereh-index 390 citations8 works total

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

author position
  • middle author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Hui Lu — 11 papers, h 9
  • Hui Lu — 8 papers, h 3
  • Hui Lu — 7 papers, h 3
  • Hui Lu — 5 papers, h 2
  • Hui Lu — 4 papers, h 6
  • Hui Lu — 3 papers, h 4

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 citedAO-DETR: Anti-Overlapping DETR for X-Ray Prohibited Items Detection

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

collaborators

4 papers

cs.CV2025

FOAM: A General Frequency-Optimized Anti-Overlapping Framework for Overlapping Object Perception

Mingyuan Li, Tong Jia, Han Gu +7

Overlapping object perception aims to decouple the randomly overlapping foreground-background features, extracting foreground features while suppressing background features, which…

cs.CV2025

CSPCL: Category Semantic Prior Contrastive Learning for Deformable DETR-Based Prohibited Item Detectors

Mingyuan Li, Tong Jia, Hao Wang +5

Prohibited item detection based on X-ray images is one of the most effective security inspection methods. However, the foreground-background feature coupling caused by the overlapp…

cs.CV2024★ 2 cited

MMCL: Correcting Content Query Distributions for Improved Anti-Overlapping X-Ray Object Detection

Mingyuan Li, Tong Jia, Hui Lu +7

Unlike natural images with occlusion-based overlap, X-ray images exhibit depth-induced superimposition and semi-transparent appearances, where objects at different depths overlap a…

cs.CV2024★ 2 cited

AO-DETR: Anti-Overlapping DETR for X-Ray Prohibited Items Detection

Mingyuan Li, Tong Jia, Hao Wang +4

Prohibited item detection in X-ray images is one of the most essential and highly effective methods widely employed in various security inspection scenarios. Considering the signif…

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