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L. Wu

4 papers hereh-index 4110 citations8 works total

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

author position
  • middle author4

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

fields
  • cs.CV3
  • cs.CE1
same name
  • L. Wu — 123 papers, h 43
  • L. Wu — 108 papers, h 30
  • L. Wu — 99 papers, h 16
  • L. Wu — 82 papers, h 10
  • L. Wu — 69 papers, h 17
  • L. Wu — 12 papers, h 3

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
20232025
most citedDe novo protein design using geometric vector field networks

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

collaborators

4 papers

cs.CV2025

Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization

Jingqi Wu, Hanxi Li, Lin Yuanbo Wu +3

Industrial product inspection is often performed using Anomaly Detection (AD) frameworks trained solely on non-defective samples. Although defective samples can be collected during…

cs.CV2025

Self-Navigated Residual Mamba for Universal Industrial Anomaly Detection

Hanxi Li, Jingqi Wu, Lin Yuanbo Wu +4

In this paper, we propose Self-Navigated Residual Mamba (SNARM), a novel framework for universal industrial anomaly detection that leverages ``self-referential learning'' within te…

cs.CV2024

Boosting Box-supervised Instance Segmentation with Pseudo Depth

Xinyi Yu, Ling Yan, Pengtao Jiang +4

The realm of Weakly Supervised Instance Segmentation (WSIS) under box supervision has garnered substantial attention, showcasing remarkable advancements in recent years. However, t…

cs.CE2023★ 2 cited

De novo protein design using geometric vector field networks

Weian Mao, Muzhi Zhu, Zheng Sun +4

Innovations like protein diffusion have enabled significant progress in de novo protein design, which is a vital topic in life science. These methods typically depend on protein st…

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