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Donghwan Kim

4 papers hereh-index 3108 citations5 works total

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

author position
  • middle author2
  • last author2

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

fields
  • cs.CL2
  • cs.CV2
same name
  • Donghwan Kim — 12 papers, h 14
  • Donghwan Kim — 6 papers, h 6
  • Donghwan Kim — 6 papers, h 3
  • Donghwan Kim — 3 papers, h 1
  • Donghwan Kim — 3 papers, h 0
  • Donghwan Kim — 3 papers, h 0

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
20202023
most citedHierarchical Text Classification As Sub-Hierarchy Sequence Generation

9 citations · 15 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 3 cited

FourierHandFlow: Neural 4D Hand Representation Using Fourier Query Flow

Jihyun Lee, Junbong Jang, Donghwan Kim +2

Recent 4D shape representations model continuous temporal evolution of implicit shapes by (1) learning query flows without leveraging shape and articulation priors or (2) decoding…

cs.CL2021★ 9 cited

Hierarchical Text Classification As Sub-Hierarchy Sequence Generation

SangHun Im, Gibaeg Kim, Heung-Seon Oh +2

Hierarchical text classification (HTC) is essential for various real applications. However, HTC models are challenging to develop because they often require processing a large volu…

cs.CV2020★ 3 cited

PAM:Point-wise Attention Module for 6D Object Pose Estimation

Myoungha Song, Jeongho Lee, Donghwan Kim

6D pose estimation refers to object recognition and estimation of 3D rotation and 3D translation. The key technology for estimating 6D pose is to estimate pose by extracting enough…

cs.CL2020

Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs

Dong Bok Lee, Seanie Lee, Woo Tae Jeong +2

One of the most crucial challenges in question answering (QA) is the scarcity of labeled data, since it is costly to obtain question-answer (QA) pairs for a target text domain with…

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