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J. Moon

26 papers hereh-index 283.7k citations209 works total

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

author position
  • middle author1
  • last author25

Across the 26 of 26 papers where every author was matched, so the position is known.

fields
  • cs.IT11
  • cs.LG6
  • cs.CV4
  • cs.DC2
  • cs.NI2
  • eess.SP1
same name
  • J. Moon — 18 papers, h 40
  • J. Moon — 16 papers, h 16
  • J. Moon — 4 papers, h 20
  • J. Moon — 4 papers, h 6
  • J. Moon — 4 papers
  • J. Moon — 3 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

activity
20132023
most citedTapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning

78 citations · 84 across the 12 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023

Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization

Jungwuk Park, Dong-Jun Han, Soyeong Kim +1

In domain generalization (DG), the target domain is unknown when the model is being trained, and the trained model should successfully work on an arbitrary (and possibly unseen) ta…

cs.CV2022★ 1 cited

Task-Adaptive Feature Transformer with Semantic Enrichment for Few-Shot Segmentation

Jun Seo, Young-Hyun Park, Sung Whan Yoon +1

Few-shot learning allows machines to classify novel classes using only a few labeled samples. Recently, few-shot segmentation aiming at semantic segmentation on low sample data has…

cs.CV2020

Task-Adaptive Feature Transformer for Few-Shot Segmentation

Jun Seo, Young-Hyun Park, Sung-Whan Yoon +1

Few-shot learning allows machines to classify novel classes using only a few labeled samples. Recently, few-shot segmentation aiming at semantic segmentation on low sample data has…

cs.CV2020

CAFENet: Class-Agnostic Few-Shot Edge Detection Network

Young-Hyun Park, Jun Seo, Jaekyun Moon

We tackle a novel few-shot learning challenge, which we call few-shot semantic edge detection, aiming to localize crisp boundaries of novel categories using only a few labeled samp…

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