Sungyeon Kim

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

(+82) 10-5408-3407   |   sungyeon.kim@postech.ac.kr

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

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

    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
  • Researched on deep metric learning and pose estimation.
    • Daegu, S.Korea
    Dec. 2016 - Jan. 2018

    Future Automotive Technology Research Center, DGIST

    Undergraduate Intern
  • 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
  • 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

    Publications

    2022

    Cross-Domain Ensemble Distillation for Domain Generalization

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

    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

    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

    Paper Code Project Page Bibtex

    2021

    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

    Paper Code Project Page Bibtex

    2020

    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

    2019

    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)

    Paper Code Project Page Bibtex

    Academic Activities

      Awards & Honors

    2022   Gold Prize, IPIU Best Paper Award - Offline Active Domain Adaptation
    2021   2nd place Prize, ICT Paper contest - Deep Metric Learning Beyond Binary Supervision
          Winning, SKT AI Fellowship
          Winning, POSTECHIAN Fellowship
          Grand Prize, IPIU Best Paper Award - Embedding Transfer with Label Relaxation for Improved Metric Learning
    2020   Winning, Naver Ph.D Fellowship
          Winning, Qualcomm Innovation Fellowship Korea - Deep Metric Learning Beyond Binary Supervision

      Reviewer

    2022   International Conference on Machine Learning (ICML)
          IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Outstanding Reviewer)
          Association for the Advancement of Artificial Intelligence (AAAI)
    2021   International Conference on Computer Vision (ICCV), 2021
          The Machine Vision Applications (MVA), 2021
    2020   International Conference on Pattern Recognition (ICPR), 2020