Minsik Jeon

I am a Robotics & Computer Vision researcher at the Agency for Defense Development (ADD) in the South Korea. My research interests lie in computer vision and robotics, with a special focus on robot perception that is generalizable and adaptable under diverse environments. I completed my bachelor's degree (Summa Cum Laude) in School of Computing at KAIST (Korea Advanced Institute of Science and Technology).

Email / Scholar / LinkedIn OWODD_Project

Research Interests

I am interested in the intersection of computer vision and robotics, with the goal of developing robust perception algorithms for robots across diverse environments. I am particularly interested in methods to learn generalizable features from unlabeled and multimodal datasets, as well as adaptation methods to adjust the models to new target domains.
My current & future interests are as follows:

● Domain Adaptation & Generalization
● Multi-modal, Open-world perception
● Self-supervised Learning
● Uncertainty-aware perception
● Off-road applications in robotics

Education

• Korea Advanced Institute of Science and Technology (KAIST), 2018.03-2022.02

● B.S. in Computer Science, Electrical Engineering (Double Major)

● GPA: 4.01/4.30 , Summa Cum Laude ; Dean's List 2020 Fall, 2021 Spring, 2021 Fall

● Gyeonggi Science High School for Gifted Students, 2015.03-2018.02

● High school for talented students in math and science

Publications

DA-RAW: Domain Adaptive Object Detection for Real-World Adverse Weather Conditions
Minsik Jeon*, Junwon Seo*, Jihong Min
IEEE International Conference on Robotics and Automation (ICRA), 2024.
project page / video / arXiv

An UDA framework for object detection that can effectively adapt to real-world adverse weather conditions by addressing Style & Weather gaps separately.

Projects

	Adaptive Path Planning Based on Situational Awareness and Dynamic Model Learning Agency for Defense Development, 2023-Present Developing perception and control algorithms for off-road navigation: Robust moving object detection & tracking in off-road environment, semantic terrain classification map.
	Unmanned reconnaissance vehicles development Agency for Defense Development, 2023 Developed an LiDAR-IR fusion method for robust object detection under visibility-constrainted scenarios.
	Deformable Object Recognition Technology Agency for Defense Development, 2022-2023 Developed an open-set 2D & 3D object detection method for LiDAR pointcloud.
	Indy Autonomous Challenge (IAC) USRG @ KAIST (Advised by Prof. David Hyunchul Shim), 2021 Participated in the Indy Autonomous Challenge (IAC), the first autonomous car racing competition to be held in Indianapolis, as an intern for Team KAIST. As part of a perception team, I tested algorithms using camera and lidar in a simulation environment.
	Microscopy Image Artifact Removal & Superresolution NICA Lab @ KAIST (Advised by Prof. Young-Gyu Yoon), 2021 Developed a removal network that addresses the line artifact of SCAPE microscopy image, using CycleGAN-like model and transferring the image into a CFM style.
	Performance and Operation Analysis of On-Board RAID SK Hynix, 2020 In Performance analysis team, configured On-board RAID using SSDs and conducted performance evaluations for each RAID option.

Template from Jon Barron's wonderful work.