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Woo Jae Kim

Ph.D. Candidate

School of Computing, KAIST


CV | Google Scholar | GitHub


I am a Ph.D. candidate in Scalable Graphics, Vision, and Robotics (SGVR) Lab at KAIST advised by Prof. Sung-Eui Yoon. I received my M.S. degree in Computer Science from KAIST and received my B.S. degree in Computer Science from KAIST in 2021 with minor in Electrical Engineering. I am also a recipient of the Qualcomm Innovation Fellowship 2023.

My main research area is Adversarial Machine Learning focused on the computer vision domain. I believe that it is imperative to diagnose the vulnerability of AI and to improve their robustness against malicious threats in order to ensure their safe deployments in the real world. Towards this goal, I focus on (1) devising practical adversarial attacks that can effectively diagnose the vulnerability of AI models and (2) building efficient and universal adversarial defense frameworks.

I am actively seeking for industrial internship positions. Please feel free to contact me for any potential opportunities!

Contact

  • wkim97 [at] kaist.ac.kr

  • Bldg E3-1, Rm 3446, 291 Daehak-ro, Yuseong-gu, Daejeon, Korea, 34141

Education

  • Ph.D in Computer Science, KAIST

    - Advisor: Sung-Eui Yoon

    Mar. 2023 - Current

  • M.S. in Computer Science, KAIST

    - Advisor: Sung-Eui Yoon

    Mar. 2021 - Feb. 2023

  • B.S. in Computer Science, KAIST

    - Minor in Electrical Engineering

    Sep. 2016 - Feb. 2021

News

  • [Jan 2024] Our work on adversarial defense is invited for a talk at Qualcomm Korea.
  • [Nov 2023] I received the Qualcomm Innovation Fellowship!
  • [Jul 2023] Our work on adversarial defense is invited for oral and poster presentations at KCCV 2023.
  • [Jul 2023] One paper is accepted to ICCV 2023.
  • [Feb 2023] One paper is accepted to CVPR 2023 as a highlights paper.
  • [Feb 2023] One paper is accepted to i3D 2023.
  • [Jun 2022] One paper is accepted to ICIP 2022 as an oral paper.
  • [Mar 2022] One paper is accepted to CVPR 2022.
  • [Jan 2022] One paper is accepted to ICASSP 2022.

Publications

  • Towards Content-based Pixel Retrieval in Revisited Oxford and Paris

    Guoyuan An, Woo Jae Kim, Saelyne Yang, Rong Li, Yuchi Huo, and Sung-Eui Yoon

    ICCV 2023

    [Project] [Paper] [Datasets and Code] [Interactive Tools]

  • Feature Separation and Recalibration for Adversarial Robustness

    Woo Jae Kim, Yoonki Cho, Junsik Jung, and Sung-Eui Yoon

    CVPR 2023 Highlights paper (~2.5% acceptance rate)

    [Project] [Paper] [Code]

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

    Kyubeom Han, Olivia G. Odenthal, Woo Jae Kim, and Sung-Eui Yoon

    i3D 2023

    also published at Proceedings of the ACM on Computer Graphics and Interactive Techniques (PACMCGIT)

    [Project] [Paper] [Code]

  • Diverse Generative Perturbations on Attention Space for Transferable Adversarial Attacks

    Woo Jae Kim, Seunghoon Hong, and Sung-Eui Yoon

    ICIP 2022 Oral paper (~10% acceptance rate)

    [Project] [Paper] [Code]

  • Part-based Pseudo Label Refinement for Unsupervised Person Re-identification

    Yoonki Cho, Woo Jae Kim, Seunghoon Hong, and Sung-Eui Yoon

    CVPR 2022

    [Project] [Paper] [Code]

  • Deep Video Inpainting Guided by Audio-Visual Self-Supervision

    Kyuyeon Kim, Junsik Jung*, Woo Jae Kim*, and Sung-Eui Yoon (* equal contributions)

    ICASSP 2022

    [Project] [Paper] [Code]

Awards & Honors

  • Winner, Qualcomm Innovation Fellowship, 2023 ($4000)
  • Paper Award, 34th Workshop on Image Processing and Image Understanding (IPIU), 2022
  • Best Teaching Assistant Award, School of Computing, KAIST, 2021 & 2023
  • Grand Prix (1st place), Undergraduate Research Program, KAIST, 2021
  • National Government Fellowship, South Korea Government, 2016 - Present

Invited Talks & Presentations

  • Invited Talk on adversarial robustness, Qualcomm Korea, 2024
  • Invited Presentation on adversarial robustness, Korean Conference on Computer Vision (KCCV), 2023

Experiences

Reviewer

  • CVPR (2023)
  • ICCV (2023)