I am a Ph.D student advised by Prof. In So Kweon in EE department, KAIST. I worked as a fulltime research intern in computer vision group at Qualcomm Research Austria.
My research interest are robust visual perception technologies for autonomous driving in day and night. I have broad interests about various computer vision algorithm for autonomous driving, e.g. object detection, segmentation, depth estimation, etc. I have been pursuing various computer vision algorithms to turn ultimate AI-powered sensors into reality.
Ph.D in Computer Vision
MS in Computer Vision, 2014
BS in Electronic Engineering, 2012
This dataset contains various illumination conditions (day, night, sunset, and sunrise) of multimodal data, which are of particular interest in autonomous driving-assistance tasks such as localization (place recognition, 6D SLAM), moving object detection (pedestrian or car) and scene understanding (drivable region).
We developed imaging hardware consisting of a color camera, a thermal camera and a beam splitter to capture the aligned multispectral (RGB color + Thermal) images. With this hardware, we captured various regular traffic scenes at day and night time to consider changes in light conditions.
Depth Estimation Based on Thermal Image, and Neural Network Learning Method Korea, Pending (10-2017-0023475), Feb 2017.
Pattern Board for Geometrical Calibration in Multi-spectral Camera System Korea, Pending (10-2016-0122950), Sep 2016.
Thermal Image Enhancement using Deep Learning Algorithm Korea, Pending (10-2016-0100058), Aug 2016.
Detecting Smoke from Image US20150030203 (Filed on May 2014).
Honorable mention ($ 2,000 / Accept rate ~6.5%), The 24th HumanTech Paper Award, Samsung, Feb 2018
Gold prize ($ 10,000 / Accept rate 0.7%), The 23th HumanTech Paper Award, Samsung, Feb 2017
Bronze prize, Korea Invention Patent Exhibition (KINPEX), Dec 2016
1st place, NVidia Deep Learning Contest, NVidia Korea, Nov 2016