Jungwan Woo

Jungwan Woo

Ph.D. student

About me

I’m Jungwan Woo, currently pursuing a Ph.D. in Computer Vision at DGIST. My primary research focuses on developing real-world autonomous driving technologies by integrating AI into robotic systems to enable their operation in everyday environments. I am particularly interested in the intersection of AI, robotics, and perception tasks in real-world scenarios. I’m conducting my research under my advisor, Prof. Sunghoon Im.

Publications

Flow4D: Leveraging 4D Voxel Network for LiDAR Scene Flow Estimation

Jaeyeul Kim, Jungwan Woo, Ukcheol Shin, Jean Oh, Sunghoon Im
Arxiv, 2024. Winner of the Argoverse 2 LiDAR Scene Flow Challenge at CVPR 2024 WAD
Paper

Rethinking LiDAR Domain Generalization: Single Source as Multiple Density Domains

Jaeyeul Kim*, Jungwan Woo*, Jeonghoon Kim, Sunghoon Im
European Conference on Computer Vision (ECCV), 2024.
Paper

Density-aware Domain Generalization for LiDAR Semantic Segmentation

Jaeyeul Kim*, Jungwan Woo*, Ukcheol Shin, Jean Oh, Sunghoon Im
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024.
Paper

Motion Forecasting via Coordinate Transformations and Object Trajectory Modifications

Jungwan Woo*, Jaeyeul Kim*, Sunghoon Im
CVPR Workshop on Autonomous Driving (CVPRw), 2023. (2nd place in the challenge)
Paper

LiDAR 3D Object Detection via Self-Training and Knowledge Distillation

Jungwan Woo*, Jaeyeul Kim*, Sunghoon Im
ECCV Workshop on 3D Perception for Autonomous Driving (ECCVw), 2022. (3rd place in the challenge)
Paper

RVMOS: Range-View Moving Object Segmentation Leveraged by Semantic and Motion Features

Jaeyeul Kim*, Jungwan Woo*, Sunghoon Im
IEEE Robotics and Automation Letters (RA-L / IROS), 2022.
Paper

Awards and Achievements

  • Winner, Argoverse LiDAR Scene Flow Challenge at CVPR WAD, 2024.
  • DGIST Post-Graduate Research Abroad Award (DPRAA), 2024.
    • Visiting Researcher at Carnegie Mellon University
  • 1st place, Autonomous Driving A.I. challenge (organized by MOLIT 국토교통부), 2023.
  • Honorable Mention, Argoverse Forecasting Challenge at CVPR WAD, 2023.
  • Best Robot Vision Paper Award, Asian Federation of Computer Vision (AFCV), 2023.
  • 2nd place, Autonomous Driving A.I. challenge (organized by MOLIT 국토교통부), 2022.
  • 3rd place, ECCV Workshop on 3D Perception for Autonomous Driving, 2022.

Education

M.S. - Ph.D. Integrated Course in Electrical Engineering and Computer Sciences (EECS), DGIST, Korea
February 2019 – Present (Advisor: Prof. Sunghoon Im)

Visiting Researcher, Carnegie Mellon University (CMU), Pittsburgh, PA, USA
January 2024 – May 2024

Summer Session (8 credits), Stanford University, CA, USA
June 2015 – July 2015 (Supported by DGIST Freshmen Global Leadership Program, FGLP)

Bachelor of Convergence Science, DGIST, Korea
March 2015 – February 2019

Skills

  • Programming Languages: Python, C++
  • Frameworks and Tools: Pytorch, OpenCV, ROS