Sungwon Hwang

M.S Candidate


CV | Google Scholar

I am a M.S student advised by Professor Hyun Myung at KAIST.

My research interests lie in machine learning and computer vision, with particular focus on deep understanding of 3D point clouds. I am currently focused on devising a deep neural network that can understand 3D point cloud representation of urban scenes collected from LiDAR. My ultimate goal is to enable accurate and real-time segmentation of point cloud scenes applicable for autonomous driving. My previous published works span point cloud registration algorithm, dynamic object removing algorithm in 3D map consturcted with SLAM, and graph-based rotation invariant representation learning.


  • shwang.14 [at] kaist.ac.kr

  • E3-2, 3240, 291 Daehak-ro, Yuseong-gu, Daejeon, Korea, 34141


  • B.S in Mechanical Engineering, 2020

    KAIST, Korea


  • Equivariance-bridged SO(2)-Invariant Representation Learning using Graph Convolutional Network

    Sungwon Hwang, Hyungtae Lim, Hyun Myung

    BMVC 2021 (Acceptance rate: 437/1206 ≈ 36%)

    [ Paper / Code ]

  • ERASOR: Egocentric Ratio of Psuedo Occupancy-based Dynamic Object Removal for Static 3D Point Cloud Map Building

    Hyungtae Lim, Sungwon Hwang, Hyun Myung

    IEEE RA-Letters (ICRA '21 Option)

    [ Paper / Code ]

  • Normal Distributions Transform is Enough: Real-time 3D Scan Matching for Pose Correction of Mobile Robot

    under Large Odometry Uncertainties

    Hyungtae Lim*, Sungwon Hwang*, Sungjae Shin, Hyun Myung (* equal contribution)

    ICCAS 2020

    [ Paper / Video ]


  • Student Best Paper Award, ICCAS '20

Academic Activities


  • IEEE Robotics and Automation Letters (ICRA '21 option)