Sunmin Lee

me/dancing_to_freedom.jpg

Hi, I’m Sunmin👋. I am a Ph.D student in Computer Science and Engineering at Seoul National University. I am fortunate enough to be advised by Prof. Jungdam Won and previously by Prof. Jehee Lee.

I am broadly interested in understanding human movements and creating a virtual agent that moves like us. It includes, but is not limited to, character animation, machine learning and robotics.

News

Sep 2024 I’m honored to be named a Yulchon AI Star.
Aug 2024 I’m excited to start an internship at NVIDIA Toronto AI Lab.
May 2024 I’m honored to be recognized as a WiGRAPH Rising Star.
Aug 2023 Our Paper SAME is accepted to Siggraph Asia 2023. See you in Sydney!
Jul 2023 I’m honored to recieve ACM Siggraph Conference Grant.
Jun 2023 - Nov 2023 Excited to start a return internship at Meta Realitity Labs Research.
Apr 2023 Our Paper QuestEnvSim is accepted to Siggraph 2023. See you in LA!
Aug 2022 - Feb 2023 Had wonderful six months at Meta Realitity Labs Research

Publications

  1. same.gif
    SAME: Skeleton-Agnostic Motion Embedding for Character Animation
    Sunmin Lee, Taeho Kang, Jungnam Park, Jehee Lee, and Jungdam Won
    ACM SIGGRAPH ASIA 2023 Conference Proceedings
  2. questenvsim.gif
    QuestEnvSim: Environment-Aware Simulated Motion Tracking from Sparse Sensors
    Sunmin Lee, Sebastian Starke, Yuting Ye, Jungdam Won, and Alexander Winkler
    ACM SIGGRAPH 2023 Conference Proceedings
  3. afamily.gif
    Learning a family of motor skills from a single motion clip
    Seyoung Lee, Sunmin Lee, Yongwoo Lee, and Jehee Lee
    ACM Transactions on Graphics (SIGGRAPH 2021)
  4. tcr.gif
    Learning Time-Critical Responses for Interactive Character Control
    Kyungho Lee, Sehee Min, Sunmin Lee, and Jehee Lee
    ACM Transactions on Graphics (SIGGRAPH 2021)
  5. icc.gif
    Learning Predict-and-Simulate Policies From Unorganized Human Motion Data
    Soohwan Park, Hoseok Ryu, Seyoung Lee, Sunmin Lee, and Jehee Lee
    ACM Transactions on Graphics (SIGGRAPH ASIA 2019)
  6. FURL
    FURL: Fixed-memory and uncertainty reducing local triangle counting for multigraph streams
    Minsoo Jung, Yongsub Lim, Sunmin Lee, and U. Kang
    Data Mining and Knowledge Discovery (DMKD) 2019