World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
6945
World Ranking
7656
National Ranking
72

Overview

Gunhee Kim is affiliated with Seoul National University in South Korea and has an extensive publication record primarily in the field of computer science. Their research contributions are concentrated in areas including artificial intelligence, computer vision and pattern recognition, and signal processing.

The scientist's work spans multiple subfields of computer science, with a particular focus on:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Civil and Structural Engineering
  • Cognitive Neuroscience

They have contributed to research on a variety of topics. Notable themes in their work include:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Natural Language Processing Techniques
  • Video Analysis and Summarization
  • Music and Audio Processing
  • Advanced Image and Video Retrieval Techniques

Gunhee Kim's frequent publication venues reflect a focus on computer science and related disciplines, with the most publications appearing in the following conferences and journals:

  • arXiv (Cornell University), 49 publications
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 4 publications
  • Proceedings of the AAAI Conference on Artificial Intelligence, 2 publications
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 1 publication
  • Scientific Reports, 1 publication

The scientist has collaborated frequently with several coauthors, including:

  • Youngjae Yu (13 coauthored publications)
  • Heeseung Yun (12 coauthored publications)
  • Soochan Lee (6 coauthored publications)
  • Chris Dongjoo Kim (5 coauthored publications)
  • Jaehyeon Son (5 coauthored publications)

Some of Gunhee Kim's recent papers illustrate the range of their research interests and contributions:

  • "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning," 2020, arXiv (Cornell University), cited 94 times
  • "Dual Compositional Learning in Interactive Image Retrieval," 2021, Proceedings of the AAAI Conference on Artificial Intelligence, cited 75 times
  • "Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes," 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, cited 56 times
  • "Pano-AVQA: Grounded Audio-Visual Question Answering on 360° Videos," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV), cited 53 times
  • "Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea," 2020, Scientific Reports, cited 43 times

Best Publications

  • Enrichment of microbial community generating electricity using a fuel-cell-type electrochemical cell

    B. H. Kim;H. S. Park;H. S. Park;H. J. Kim;G. T. Kim

  • TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering

    Yunseok Jang;Yale Song;Youngjae Yu;Youngjin Kim

  • Distributed cosegmentation via submodular optimization on anisotropic diffusion

    Gunhee Kim;Eric P. Xing;Li Fei-Fei;Takeo Kanade

  • A Joint Sequence Fusion Model for Video Question Answering and Retrieval

    Youngjae Yu;Jongseok Kim;Gunhee Kim

  • Better to Follow, Follow to Be Better: Towards Precise Supervision of Feature Super-Resolution for Small Object Detection

    Junhyug Noh;Wonho Bae;Wonhee Lee;Jinhwan Seo

  • End-to-End Concept Word Detection for Video Captioning, Retrieval, and Question Answering

    Youngjae Yu;Hyungjin Ko;Jongwook Choi;Gunhee Kim

  • Joint Summarization of Large-Scale Collections of Web Images and Videos for Storyline Reconstruction

    Gunhee Kim;Leonid Sigal;Eric P. Xing

  • Attend to You: Personalized Image Captioning with Context Sequence Memory Networks

    Cesc Chunseong Park;Byeongchang Kim;Gunhee Kim

  • On multiple foreground cosegmentation

    Gunhee Kim;Eric P. Xing

  • Unsupervised modeling of object categories using link analysis techniques

    Gunhee Kim;C. Faloutsos;M. Hebert

  • Unsupervised Detection of Regions of Interest Using Iterative Link Analysis

    Gunhee Kim;Antonio Torralba

  • A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

    Kyung Don Yoo;Junhyug Noh;Hajeong Lee;Dong Ki Kim

  • Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue

    Byeongchang Kim;Jaewoo Ahn;Gunhee Kim

  • A Hierarchical Latent Structure for Variational Conversation Modeling

    Yookoon Park;Jaemin Cho;Gunhee Kim

  • A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning

    Soochan Lee;Junsoo Ha;Dongsu Zhang;Gunhee Kim

  • A Read-Write Memory Network for Movie Story Understanding

    Seil Na;Sangho Lee;Jisung Kim;Gunhee Kim

  • Abstractive Summarization of Reddit Posts with Multi-level Memory Networks

    Byeongchang Kim;Hyunwoo Kim;Gunhee Kim

  • Expressing an image stream with a sequence of natural sentences

    Cesc Chunseong Park;Gunhee Kim

  • Rethinking Class Activation Mapping for Weakly Supervised Object Localization

    Wonho Bae;Junhyug Noh;Gunhee Kim

  • Big/little deep neural network for ultra low power inference

    Eunhyeok Park;Dongyoung Kim;Soobeom Kim;Yong-Deok Kim

  • Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors

    Junhyug Noh;Soochan Lee;Beomsu Kim;Gunhee Kim

  • AudioCaps: Generating Captions for Audios in The Wild.

    Chris Dongjoo Kim;Byeongchang Kim;Hyunmin Lee;Gunhee Kim

Frequent Co-Authors

Eric P. Xing
Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence
Leonid Sigal
Leonid Sigal University of British Columbia
Thomas M. Breuel
Thomas M. Breuel Nvidia (United States)
Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Martial Hebert
Martial Hebert Carnegie Mellon University
Gal Chechik
Gal Chechik Bar-Ilan University
Jan Kautz
Jan Kautz Nvidia (United States)
Hao Zhang
Hao Zhang Simon Fraser University
Li Fei-Fei
Li Fei-Fei Stanford University

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