About me

I’m Youngseok Kim (김영석), currently a Computer Vision Research Engineer at 42dot. I am developing a perception model for autonomous driving system and I am in charge of 3D object detection using camera and radar.

I obtained my PhD degree from KAIST in 2023, advised by Prof. Dongsuk Kum and I got KAIST College of Engineering PhD Dissertation Award. My research interest lies in 3D computer vision and its application to autonomous driving. Specifically, I am focusing on developing a robust and cost-effective 3D perception system using camera and radar, self-supervised and active learning to make the cost- and time-consuming training process efficient.


Publications

  • CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception
    Youngseok Kim, Juyeb Shin, Sanmin Kim, In-jae Lee, Jun Won Choi, Dongsuk Kum
    IEEE/CVF International Conference on Computer Vision (ICCV), 2023
    [Paper] [Code] [Video Demo] [Poster] [Presentation]
     -   Preliminary version is published in ICLR SR4AD Workshop [Paper] [Presentation]
     -   Presented at 2023 KAIST Future Mobility Conference [Presentation (Korean)]
    Ranked 1st among camera-radar methods on nuScenes as of March 2023
  • Predict to Detect: Prediction-guided 3D Object Detection using Sequential Images
    Sanmin Kim, Youngseok Kim, In-Jae Lee, Dongsuk Kum
    IEEE/CVF International Conference on Computer Vision (ICCV), 2023
    [Paper] [Code]

  • CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformer
    Youngseok Kim, Sanmin Kim, Jun Won Choi, Dongsuk Kum
    AAAI Conference on Artificial Intelligence (AAAI), 2023
    [Paper] [Video Demo] [Poster] [Presentation]
     -   Introduced in 2023 KAIST Annual R&D Report [Link (English)] [Link (Korean)]
     -   Ranked 1st among camera-radar methods on nuScenes as of July 2022

  • Joint Semi-Supervised and Active Learning via 3D Consistency for 3D Object Detection
    Sihwan Hwang, Sanmin Kim, Youngseok Kim, Dongsuk Kum
    IEEE/RSJ International Conference on Robotics and Automation (ICRA), 2023
    [Paper] [Video Demo]

  • Boosting Monocular 3D Object Detection with Object-Centric Auxiliary Depth Supervision
    Youngseok Kim, Sanmin Kim, Sangmin Sim, Jun Won Choi, Dongsuk Kum
    IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2022 (Impact Factor 9.551)
    [Paper] [Video Demo]
     -   Ranked 1st/3rd among KITTI monocular BEV/3D detection as of 2021 April
    Introduced in 2021 KAIST breakthroughs [Link]
  • Sequential Image-based 3D Object Detection with Location Refinement
    Sangmin Sim, Youngseok Kim, Dongsuk Kum
    IEEE International Conference on Pattern Recognition (ICPR), 2022
    [Paper]

  • GRIF Net: Gated Region of Interest Fusion Network for Robust 3D Object Detection from Radar Point Cloud and Monocular Image
    Youngseok Kim, Jun Won Choi, Dongsuk Kum
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
    [Paper] [Video Demo] [Presentation]
     -   Presented at Seoul Mobility Show 2021 Conference

  • Low-level Sensor Fusion Network for 3D Vehicle Detection using Radar Range-Azimuth Heatmap and Monocular Image
    Jinhyeong Kim*, Youngseok Kim*, Dongsuk Kum
    Asian Conference on Computer Vision (ACCV), 2020
    [Paper] [Presentation]

  • Deep Learning based Vehicle Position and Orientation Estimation via Inverse Perspective Mapping Image
    Youngseok Kim, Dongsuk Kum
    IEEE Intelligent Vehicles Symposium (IV), 2019
    [Paper] [Video Demo] [Poster]
    Oral presentation, 5.8% acceptance rate for oral-presentation papers

Other Publications

  • Autonomous Driving Technology Trend and Future Outlook: Powered by Artificial Intelligence
    Sanmin Kim, Youngseok Kim, Hyeongseok Jeon, Dongsuk Kum, Kibeom Lee
    Transactions of Korean Society of Automotive Engineers (Trans. KSAE), 2022

  • Vehicle Distance Estimation using Convolutional Neural Network on Inverse Perspective Mapping Image
    Youngseok Kim, Dongsuk Kum
    Korean Society of Automotive Engineers Annual Conference (KSAE), 2019

  • Fault Tolerant Vehicle Detection Using Camera-LiDAR Sensor Fusion: Multi-channel Faster R-CNN
    Youngseok Kim, Dongsuk Kum
    Korean Society of Automotive Engineers Annual Conference (KSAE), 2018


Patents

  • Electronic Device for Perceiving Three-Dimension Environment based on Camera and Radar, and Operating Method Thereof
    Dongsuk Kum, Youngseok Kim
    US, Application Number: 18/502,678
    KR, Application Number: 10-2023-0096379

  • Electronic Device for Camera and Radar Sensor Fusion-based Three-dimensional Object Detection and Operating Method Thereof
    Dongsuk Kum, Youngseok Kim
    US, Registration Number: 11,754,701 [Patent]
    DE, PCT, Application Number: 10 2021 106 518.6, PCT/KR2021/002916
    KR, Registration Number: 10-2168753-0000

  • Simultaneous Traffic Participants Detection and Localization via Bird’s Eye View Image
    Dongsuk Kum, Youngseok Kim
    KR, Registration Number: 10-2003387-0000

  • Distance Measuring Device Using Mono Infrared Camera and Method Thereof
    Dongsuk Kum, Youngseok Kim, Seoung Jun Lee
    KR, Registration Number: 10-1918887-0000


Professional Services

Conference Reviewer for AAAI, CVPR, ECCV, ICRA, IROS, ITSC, IV
Journal Reviewer for IJAT, NeuroComputing, RA-L, T-ITS, T-IV, TPAMI


Last updated: April 20, 2024