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Hi, This is @Taeyoung96! πŸ‘‹

🌱 Education

πŸ”΅ M.S in Vehicle Convergence Engineering at CILAB from Yonsei University, Seoul, South Korea (2022.3 ~ 2024.2)
πŸ”΅ B.S in Robotics from Kwangwoon University, Seoul, South Korea (2016.3 ~ 2022.2)

πŸ“™ Reasearch Interest

🟠 SLAM - Lidar SLAM, Lidar-inertial odometry, Visual SLAM, Visual-inertial odometry
🟠 Sensor Funsion - Combination of camera, LiDAR, or IMU sensor.
🟠 Computer Vision - Object Detection, Segmentation, Depth estimation, 3D reconstruction, Neural rendering

πŸš€ Careers

⚫ Research Engineer at Hyundai Motor Group, Robotics Lab (2024.2 ~ Current)
⚫ Student Intern at KIST (Korea Institute of Science and Technology), Robot Vision Lab (2020.9 ~ 2021.2)

πŸ‘€ Who wants to know more about me, click it!

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TaeYoung Kim's Projects

006939 icon 006939

'OpenCV 4둜 λ°°μš°λŠ” 컴퓨터 λΉ„μ „κ³Ό λ¨Έμ‹  λŸ¬λ‹'을 보고 주석을 달며 κ³΅λΆ€ν•˜μ˜€μŠ΅λ‹ˆλ‹€.

2021-capstone-design icon 2021-capstone-design

2021-Spring-Capstone-Design 'μ „κΈ°μ°¨ 무선 μΆ©μ „ λ‘œλ΄‡'

algorithm-study icon algorithm-study

μ‘°κΈˆμ”© κΎΈμ€€ν•˜κ²Œ μ•Œκ³ λ¦¬μ¦˜ 문제λ₯Ό ν’€λ €κ³  λ…Έλ ₯μ€‘μž…λ‹ˆλ‹€.

awesome-dev-contents icon awesome-dev-contents

β˜• μ°¨ ν•œμž”ν•˜λ©° μ¦κ²¨λ³Όλ§Œν•œ 쒋은 개발 글을 μ†Œκ°œν•΄ λ“œλ¦½λ‹ˆλ‹€.

awesome-implicit-nerf-slam icon awesome-implicit-nerf-slam

A comprehensive list of Implicit Representations and NeRF papers relating to SLAM/Robotics domain, including papers, video, codes, and related websites

baram_readme icon baram_readme

λ°”λžŒ ν”„λ‘œμ νŠΈμš© README.md 파일 μž…λ‹ˆλ‹€.

bts icon bts

From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation

cv-arxiv-daily icon cv-arxiv-daily

πŸŽ“Automatically Update CV Papers Daily using Github Actions (Update Every 12th hours)

deep-learning-from-scratch icon deep-learning-from-scratch

γ€Žλ°‘λ°”λ‹₯λΆ€ν„° μ‹œμž‘ν•˜λŠ” λ”₯λŸ¬λ‹γ€(ν•œλΉ›λ―Έλ””μ–΄, 2017)의 책을 보고 μ†ŒμŠ€μ½”λ“œλ₯Ό 보고 곡뢀λ₯Ό ν•΄λ³΄μ•˜μŠ΅λ‹ˆλ‹€.

depth-estimation-with-orb-slam2 icon depth-estimation-with-orb-slam2

20년도 ν›„λ°˜κΈ° Toy Project 'Depth estimation with ORB-SLAM2'에 λŒ€ν•œ μ†ŒμŠ€μ½”λ“œμž…λ‹ˆλ‹€.

faster-lio icon faster-lio

Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry using Parallel Sparse Incremental Voxels

fmt icon fmt

A modern formatting library

gril-calib icon gril-calib

GRIL-Calib: Targetless Ground Robot IMU-LiDAR Extrinsic Calibration Method using Ground Plane Motion Constraints

grounded-segment-anything icon grounded-segment-anything

Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

gtsam icon gtsam

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.

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