3D Vision & Robotics Lab.

3차원 비전 및 로보틱스 연구실

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3차원 비전 및 로보틱스 연구실

Our lab aims to develop cutting-edge computer vision, robotics vision, and machine (deep) learning algorithms. Specifically, our research mainly focuses on 3D computer vision with a particular focus on geometric aspects. Our goal is to give the capability to a system (e.g., robots and autonomous vehicles) to understand and interpret various data in a manner that is similar to the way humans use their senses to relate to the world around them. To achieve this goal, we focus on processing and analyzing various sensor data such as image, video, 3D point cloud, and other sensory data. Currently, we are working on the following research topics:
- 3D Computer Vision and Geometry
- Robotics Vision
- Urban Scene Understanding
- Simultaneous Localization and Mapping
- Sensor Fusion

Major research field

Computer Vision, Robotics Vision, Machine (Deep) Learning

Desired field of research

3D Reconstruction from images (SfM, SLAM, etc.), Sensor Fusion, Vision-based ADAS, Calibration, Geometry-based Deep Learning

Research Keywords and Topics

# Computer Vision
- 3D Reconstruction from images (SfM, SLAM, etc.)
# Robotics Vision
- Sensor Fusion, Vision-based ADAS, Calibration
# Machine (Deep) Learning
- Geometry-based Deep Learning

Research Publications

# IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
"Diffusion-based Signed Distance Fields for 3D Shape Generation"
J. Shim, C. Kang, Kyungdon Joo
# AAAI Conference on Artificial Intelligence (AAAI), 2023
"Pose-guided 3D Human Generation in Indoor Scene"
M. Kim, C. Kang, J. Park, Kyungdon Joo
# IEEE Transactions on Pattern Analysis and Machine Intelligence,
"Linear RGB-D SLAM for Structured Environments"
Kyungdon Joo, P. Kim, M. Hebert, I. S. Kweon and H. J. Kim, Nov. 2022. (IF: 24.314)
# IEEE Transactions on Pattern Analysis and Machine Intelligence,
"Robust and Efficient Estimation of Relative Pose for Cameras on Selfie Sticks"
Kyungdon Joo, H. Li, T.-H. Oh, and I. S. Kweon, Sep. 2022. (IF: 24.314)
# IEEE International Conference on Computer Vision (ICCV), 2021
"Learning Icosahedral Spherical Probability Map Based on Bingham Mixture Model for Vanishing Point Estimation"
H. Li*, K. Chen*, P. Kim, K.-J. Yoon, Z. Liu, Kyungdon Joo† and Y.-H. Liu†


# [Pending] “Camera and Camera Calibration Method,”
In So Kweon, Hyowon Ha, Yunsu Bok, Kyungdon Joo, Jiyoung Jung, US 15474940, 2017.
# [등록] “카메라 및 카메라 캘리브레이션 방법,”
(등록) 권인소, 하효원, 복윤수, 주경돈, 정지영, 등록번호 10-1818104-0000, 2016.


  • EE. 정보/통신
  • EE01. 정보이론
  • EE0108. 인공지능


  • 정보-지식-지능화 사회 구현
  • 012300. 인공지능/지능로봇 기술


  • 녹색기술관련 과제 아님
  • 녹색기술관련 과제 아님
  • 999. 녹색기술 관련과제 아님


  • IT 분야
  • 정보처리 시스템 및 S/W
  • 010314. 신호처리기술(영상/음성처리/인식/합성)