Gwangtak Bae
I'm a Ph.D. student at 3D Vision Lab, advised by Prof. Young Min Kim at Seoul National University (SNU). Before joining the lab, I had a great time as a Research Officer in Agency for Defense Development (ADD). I received a B.S. in Electrical Engineering from Korea Institute of Science and Technology (KAIST). I'm interested in designing robust vision systems for robots.
Contact: tak3452@{snu.ac.kr, gmail.com}
Curriculum Vitae: [CV] (updated: Jul. 2024)
News
Jul. 2024: One paper got accepted to ECCV 2024.
Jul. 2022: One paper got accepted to ECCV 2022.
Jul. 2022: Joined 3D Vision Lab @SNU.
Jun. 2022: Completed my military service in Agency for Defense Development as a Research Officer for National Defense.
Feb. 2019: Got my Bachelor's degree in Electrical Engineering at KAIST.
Publications
I^2-SLAM: Inverting Imaging Process for Robust Photorealistic Dense SLAM
Gwangtak Bae*, Changwoon Choi*, Hyeongjun Heo, Sang Min Kim, and Young Min Kim
(*Equally contributed)
European Conference on Computer Vision (ECCV), 2024
[arXiv] [paper]
SLiDE: Self-supervised LiDAR De-snowing through Reconstruction Difficulty
Gwangtak Bae, Byungjun Kim, Seongyong Ahn, Jihong Min, and Inwook Shim
European Conference on Computer Vision (ECCV), 2022
Work Experience
Research Officer, Agency for Defense Development, Daejeon, Korea
Ground Autonomy Lab
Jun. 2019 - May. 2022
Education
Seoul National University, Seoul, Korea.
Ph.D. candidate in Electrical and Computer Engineering
Sep. 2022 - present
Korea Advanced Institute of Science and Technology, Daejeon, Korea.
B.S. in Electrical Engineering
Mar. 2015 - Feb. 2019
Daegu Science High School, Daegu, Korea.
Mar. 2012 - Feb. 2015
Honors & Awards
Young Engineers Honor Society, National Academy of Engineering of Korea
through the recommendation of the President and Dean of engineering college
Research Officer for National Defense
25 selected nation-wide
Patents
KR10-2420585 Method and Apparatus for Simulating Point Cloud Data of 3D Lidar Sensor in Adverse Weather.
KR10-2405818 Method of Removing Noise, Apparatus for Removing Noise, and Computer Program for the method.
Academic Activities
Reviewer: RA-L