Sungyeon Kim

Ph.D. Candidate @ Computer Vison LAB in POSTECH.

  sungyeon.kim@postech.ac.kr

I am a Ph.D. candidate in the Computer Science and Engineering at POSTECH. I am a member of the Computer Vision Lab at POSTECH, under supervision of Professor Suha Kwak. My research interests are deep metric learning, representation learning and their applications.



News

2023. 06   📄 A paper on domain generalization is accepted in ICCV 2023
2023. 06   🎉 I won the Google PhD fellowship program 2023.
2023. 04   ⭐ Code for HIER: Metric Learning Beyond Class Labels via Hierarchical Regularization is released.
2023. 02   📄 A paper about hierarchical regularization for metric learning is accepted at CVPR 2023.

Publications

Preprints

Universal Metric Learning with Parameter-Efficient Transfer Learning

Sungyeon Kim, Donghyun Kim, Suha Kwak
Arxiv Preprint

Paper Bibtex

Conference Papers

PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization

Junhyeong Cho, Gilhyun Nam, Sungyeon Kim, Hunmin Yang, Suha Kwak
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023

Paper Project Page Bibtex

HIER: Metric Learning Beyond Class Labels via Hierarchical Regularization

Sungyeon Kim, Boseung Jeong, Suha Kwak
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Qualcomm Innovation Fellowship Finalist

Paper Code Project Page Bibtex

Cross-Domain Ensemble Distillation for Domain Generalization

Kyungmoon Lee, Sungyeon Kim, Suha Kwak
European Conference on Computer Vision (ECCV), 2022

Paper Code Bibtex

Combating Label Distribution Shift for Active Domain Adaptation

Sehyun Hwang, Sohyun Lee, Sungyeon Kim, Jungseul Ok, Suha Kwak
European Conference on Computer Vision (ECCV), 2022
IPIU Best Paper Award, BK21 Best Paper Award, Qualcomm Innovation Fellowship Winner

Paper Code Bibtex

Self-Taught Metric Learning without Labels

Sungyeon Kim, Dongwon Kim, Minsu Cho, Suha Kwak
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
BK21 Best Paper Award, Qualcomm Innovation Fellowship Winner

Paper Code Project Page Bibtex

Learning to Generate Novel Classes for Deep Metric Learning

Kyungmoon Lee, Sungyeon Kim, Seunghoon Hong, Suha Kwak
British Machine Vision Conference (BMVC), 2021

Paper Bibtex

Embedding Transfer with Label Relaxation for Improved Metric Learning

Sungyeon Kim, Dongwon Kim, Minsu Cho, Suha Kwak
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
BK21 Best Paper Award, IPIU Best Paper Award Winner

Paper Code Project Page Bibtex

Proxy Anchor Loss for Deep Metric Learning

Sungyeon Kim, Dongwon Kim, Minsu Cho, Suha Kwak
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020

Paper Code Project Page Bibtex

Deep Metric Learning Beyond Binary Supervision

Sungyeon Kim, Minkyo Seo, Ivan Laptev, Minsu Cho, Suha Kwak
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Oral Presentation (5.6% acceptance rate), Qualcomm Innovation Fellowship Winner

Paper Code Project Page Bibtex

Education

Computer Vision Lab, POSTECH (Pohang University of Science and Technology)

Ph.D Candidate at Computer Science and Engineering
  • Advised by Prof. Suha Kwak.
    • Pohang, S.Korea
    Sep. 2018 - current

    DGIST (Daegu Gyeongbuk Institute of Science and Technology)

    B.S at Undergraduate Studies
    Daegu, S.Korea
    Mar. 2014 - Feb. 2018

    Experience

    MIT-IBM Watson AI Lab

    Research Collaboration
  • Research with Donghyun Kim.
  • Researched on parameter-efficient learning and deep metric learning.
    • Cambridge, MA (Remote)
    Dec. 2022 - Current

    Vision Team, Naver

    Research Intern
  • Research with Geonmo Gu, Byungsoo Ko.
  • Researched on self-supervised learning.
    • Seongnam, S.Korea (Remote)
    Apr. 2022 - Jul. 2022

    Computer Vision Lab, POSTECH

    Research Assistant
  • Advised by Prof. Suha Kwak.
  • Researched on deep metric learning.
    • Pohang, S.Korea
    Apr. 2018 - Aug. 2018

    Vision and Learning Group, DGIST

    Undergraduate Intern
  • Advised by Prof. Suha Kwak.
  • Researched on deep metric learning and pose estimation.
    • Daegu, S.Korea
    Dec. 2016 - Jan. 2018

    Future Automotive Technology Research Center, DGIST

    Undergraduate Intern
  • Advised by Wooyoung Jung.
  • Researched on pedestrian detection in video for autonomous vehicles.
  • Implemented API for pedestrian detection utilizing PyCaffe and PyQt.
    • Daegu, S.Korea
    Jun. 2016 - Aug. 2016

    Communication and Signal Processing Lab, DGIST

    Undergraduate Intern
  • Advised by Prof. Ji-Woong Choi.
  • Researched on Muscle-computer connection systems and signal processing.
  • Developed Electromyography (EMG) signal processing tool to reduce signal noise.
  • Patented for rehabilitation program using measured EMG signals.
  • KR101648638B1, Rehabilitation program creation method for muscle treatment and
          rehabilitation program providing apparatus for performing the method
    • Daegu, S.Korea
    Mar. 2014 – Jun. 2014

    Awads & Honors

    2023
  • Google PhD Fellowship Program, Google
  • BK21 Best Paper Award, Dept.CSE, POSTECH
      Winner - Self-Taught Metric Learning without Labels
  • BK21 Best Paper Award, Dept.CSE, POSTECH
      Winner - Combating Label Distribution Shift for Active Domain Adaptation
    • 2022
  • Qualcomm Innovation Fellowship Korea, Qualcomm Technologies Inc.
      Winner - Self-Taught Metric Learning without Labels
  • Qualcomm Innovation Fellowship Korea, Qualcomm Technologies Inc.
      Winner - Combating Label Distribution Shift for Active Domain Adaptation
  • BK21 Best Paper Award, Dept.CSE, POSTECH
      Winner - Embedding Transfer with Label Relaxation for Improved Metric Learning
  • IPIU Best Paper Award, Workshop on Image Processing and Image Understanding (IPIU)
      Gold Prize - Offline Active Domain Adaptation
  • CVPR Outstanding Reviewer, IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    • 2021
  • ICT Paper contest, Etnews, Webcash Group, and KSFC
      2nd place Prize - Deep Metric Learning Beyond Binary Supervision
  • SKT AI Fellowship, SK Telecom Co., Ltd
  • POSTECHIAN Fellowship, POSTECH
  • IPIU Best Paper Award, Workshop on Image Processing and Image Understanding (IPIU)
      Grand Prize - Deep Metric Learning Beyond Binary Supervision
    • 2020
  • Naver Ph.D Fellowship, NAVER Corp.
  • Qualcomm Innovation Fellowship Korea, Qualcomm Technologies Inc.
      Winner - Deep Metric Learning Beyond Binary Supervision

    • Academic Services

    International Conference Reviewer

  • IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Outstanding Reviewer in 2022]
  • International Conference on Computer Vision (ICCV)
  • The European Conference on Computer Vision (ECCV)
  • International Conference on Machine Learning (ICML)
  • International Conference on Learning Representations (ICLR)
  • Conference on Neural Information Processing Systems (NeurIPS)
  • Association for the Advancement of Artificial Intelligence (AAAI)
  • IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Asian Conference on Computer Vision (ACCV)
  • The Machine Vision Applications (MVA)
  • International Conference on Pattern Recognition (ICPR)


    • International Journal Reviewer

  • Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE
  • International Journal of Computer Vision (IJCV), IEEE