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Han-Gyu Kim

5 papers hereh-index 398 citations9 works total

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

author position
  • middle author2
  • last author3

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CL1
same name
  • Han-gyu Kim — 6 papers, h 9
  • Han-Gyu Kim — 5 papers, h 2
  • Han-Gyu Kim — 2 papers, h 2
  • Han-Gyu Kim — 2 papers, h 7
  • Han-Gyu Kim — 1 paper, h 1

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
20212024
most citedGroup Generalized Mean Pooling for Vision Transformer

5 citations · 10 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

Intriguing Properties of Large Language and Vision Models

Young-Jun Lee, Byungsoo Ko, Han-Gyu Kim +2

Recently, large language and vision models (LLVMs) have received significant attention and development efforts due to their remarkable generalization performance across a wide rang…

cs.CV2022★ 5 cited

Group Generalized Mean Pooling for Vision Transformer

Byungsoo Ko, Han-Gyu Kim, Byeongho Heo +4

Vision Transformer (ViT) extracts the final representation from either class token or an average of all patch tokens, following the architecture of Transformer in Natural Language…

cs.CV2021★ 2 cited

Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning

Geonmo Gu, Byungsoo Ko, Han-Gyu Kim

One of the main purposes of deep metric learning is to construct an embedding space that has well-generalized embeddings on both seen (training) classes and unseen (test) classes.…

cs.CV2021★ 1 cited

Learning with Memory-based Virtual Classes for Deep Metric Learning

Byungsoo Ko, Geonmo Gu, Han-Gyu Kim

The core of deep metric learning (DML) involves learning visual similarities in high-dimensional embedding space. One of the main challenges is to generalize from seen classes of t…

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