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.
  • GPA: 3.92/4.3
  • Pohang, S.Korea
    Sep. 2018 - current

    DGIST (Daegu Gyeongbuk Institute of Science and Technology)

    B.S at Undergraduate Studies
  • GPA: 3.65/4.3
  • 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

    2021

    Learning to Generate Novel Classes for Deep Metric Learning
    for Improved Metric Learning

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

    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

    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

    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

    Academic Activities

      Awards & Honors

  • 2nd place Prize at ICT Paper contest, 2021
  • SKT AI Fellowship, 2021
  • POSTECHIAN Fellowship, 2021
  • Grand Prize at IPIU Best Paper Award, 2021 - Embedding Transfer with Label Relaxation for Improved Metric Learning
  • Naver Ph.D Fellowship, 2020
  • Qualcomm Innovation Fellowship Korea, 2020 - Deep Metric Learnign Beyond Binary Supervision
  •   Reviewer

  • IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
  • International Conference on Computer Vision (ICCV), 2021
  • The Machine Vision Applications (MVA), 2021
  • International Conference on Pattern Recognition (ICPR), 2020