Seokju Lee

Ph.D. Candidate
Robotics and Computer Vision lab.
Korea Advanced Institute of Science and Technology (KAIST)

seokju91 [at] gmail.com
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Welcome

I am a Ph.D. candidate in Robotics and Computer Vision Lab. at KAIST under the supervision of Prof. In So Kweon Ph.D. since 2016. I received the B.Sc. degree in electrical and computer engineering from UNIST, South Korea and the M.Sc. degree in the robotics program from KAIST under the supervision of Prof. David Hyunchul Shim Ph.D. in 2015. I am a research intern at Microsoft Research Asia (Beijing, China) now.



Research Interests

  • Deep Learning
    • Representation learning
    • Domain adaptation
  • Computer/Robot Vision
    • Object detection and recognition
    • Semantic segmentation
  • Autonomous Vehicles
    • Direct perception approach
    • Sensor fusion



International Conferences and Journals


2018

  • Co-domain Embedding using Deep Quadruplet Networks for Unseen Traffic Sign Recognition
    Junsik Kim, Seokju Lee, Tae-Hyun Oh, In So Kweon 
    AAAI Conference on Artificial Intelligence (AAAI), Feb 2018
    [Paper] [Project] [Patent]
    Received Best Poster Presentation Award, 30th IPIU 2018

2017

  • VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition
    Seokju Lee, Junsik Kim, Jae Shin Yoon, Seunghak Shin, Oleksandr Bailo, Namil Kim, Tae-Hee Lee, Hyun Seok Hong, Seung-Hoon Han, In So Kweon 
    IEEE International Conference on Computer Vision (ICCV), Oct 2017
    [Paper[Poster] [Project] [Patent]
    Patent in Korea (
    10-2017-0144231)

  • Pixel-Level Matching for Video Object Segmentation Using Convolutional Neural Networks
    Jae Shin Yoon, Francois Rameau, Junsik Kim, Seokju Lee, Seunghak Shin, In So Kweon
    IEEE International Conference on Computer Vision (ICCV), Oct 2017
    [Paper] [Project

  • Robust Road Marking Detection and Recognition Using Density-Based Grouping and Machine Learning Techniques
    Oleksandr Bailo, Seokju Lee, Francois Rameau, Jae Shin Yoon, In So Kweon
    IEEE Winter Conference on Applications of Computer Vision (WACV), Mar 2017
    [Paper] [Youtube]

2016

  • Fast multiple objects detection and tracking fusing color camera and 3D LIDAR for intelligent vehicles 
    Soonmin Hwang, Namil Kim, Yukyung Choi, Seokju Lee, In So Kweon
    IEEE International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Aug 2016
    [Paper] [Project]

2015

  • Rich feature hierarchies from omni-directional RGB-DI information for pedestrian detection
    Seokju Lee, Sungsik Huh, Donggeun Yoo, In So Kweon, David Hyunchul Shim
    IEEE International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Oct 2015
    [Paper] [Project]

2014

  • Development of an exploration rover platform for sample return mission
    Seokju Lee, Sungsik Huh, Sungyeon Park, David Hyunchul Shim
    IEEE International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Nov 2014
    [Paper] [Youtube]


Other Publications


  • A Flight Test for Neutralization of Enemy Position Using Intelligent Cooperative System of Heterogeneous Unmanned Vehicle System
    Hanjun Song, Seokju Lee, Sungwook Cho, and David Hyunchul Shim
    The Korean Society for Aeronautical and Space Sciences Spring Conference (KSAS), Apr 2015
    [Paper[IEEE Spectrum]

  • Development of Robotic Hand System Using Vision-Based Motion Sensor
    Seokju Lee, Hanjun Song, and David Hyunchul Shim
    The 29th Institute of Control, Robotics and Systems Annual Conference (ICROS), May 2014
    [Paper] [Project[Youtube]

  • Development of a Rover Platform for Exploration and Sample Return Mission
    Seokju Lee, Sungsik Huh, Dasol Lee, Sungwook Cho, and David Hyunchul Shim
    The Korean Society for Aeronautical and Space Sciences Spring Conference (KSAS), Apr 2014
    [Paper[Youtube]



Thesis



  • Hierarchical Pedestrian Detection Using Omnidirectional Camera and Laser Sensor Fusion
    MS Thesis, 2015.
    [Paper[Project]



Patents



  • Vanishing-Guided Lane and Road Marking Detection via Multi-Task Network
    Application date: Oct. 31, 2016 (US Provisional Application 62/414,951)




Last updated: June 15, 2018