◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

W. Kim

17 papers hereh-index 7380 citations20 works total

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

author position
  • first author4
  • middle author13

Across the 17 of 17 papers where every author was matched, so the position is known.

fields
  • cs.CV14
  • cs.GR1
  • eess.AS1
  • eess.IV1
same name
  • W. Kim — 220 papers, h 46
  • W. Kim — 40 papers
  • W. Kim — 36 papers, h 88
  • W. Kim — 9 papers, h 30
  • W. Kim — 7 papers, h 5
  • W. Kim — 6 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
20222026
most citedPart-based Pseudo Label Refinement for Unsupervised Person Re-identification

14 citations · 21 across the 16 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

eess.AS2023★ 1 cited

Deep Video Inpainting Guided by Audio-Visual Self-Supervision

Kyuyeon Kim, Junsik Jung, Woo Jae Kim +1

Humans can easily imagine a scene from auditory information based on their prior knowledge of audio-visual events. In this paper, we mimic this innate human ability in deep learnin…

cs.CV2023

Towards Content-based Pixel Retrieval in Revisited Oxford and Paris

Guoyuan An, Woo Jae Kim, Saelyne Yang +3

This paper introduces the first two pixel retrieval benchmarks. Pixel retrieval is segmented instance retrieval. Like semantic segmentation extends classification to the pixel leve…

cs.GR2023★ 1 cited

Pixel-wise Guidance for Utilizing Auxiliary Features in Monte Carlo Denoising

Kyu Beom Han, Olivia G. Odenthal, Woo Jae Kim +1

Auxiliary features such as geometric buffers (G-buffers) and path descriptors (P-buffers) have been shown to significantly improve Monte Carlo (MC) denoising. However, recent appro…

cs.CV2023★ 2 cited

Feature Separation and Recalibration for Adversarial Robustness

Woo Jae Kim, Yoonki Cho, Junsik Jung +1

Deep neural networks are susceptible to adversarial attacks due to the accumulation of perturbations in the feature level, and numerous works have boosted model robustness by deact…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.