Jongchan Park

Research Scientist @Lunit Inc.

jcpark [at] lunit.io

CV | Github | Google Scholar

I received my BS degree in Computer Science, and my MS degree in Electrical Engineering from KAIST. During my MS degree, I was advised by Prof. In So Kweon. Spent most of my childhood in China.

Interested in object recognition with deep learning.

Selected Publications

(* equal contribution)


  • Using Self-Supervised Pretext Tasks for Active Learning

John Seon Keun Yi*, Minseok Seo*, Jongchan Park, Dong-Geol Choi

European Conference for Computer Vision (ECCV) 2022


  • A Self-Supervised Sampler for Efficient Action Recognition: Real-World Applications in Surveillance System

MinSeok Seo, Donghyeon Cho, SangWoo Lee, Jongchan Park, Daehan Kim, Jaemin Lee, Jingi Ju, Hyeoncheol Noh, and Dong-Geol Choi

IEEE Robotics and Automation Letters (RA-L), presented at IEEE International Conference on Robotics and Automation (ICRA) 2022


  • Reducing Domain Gap by Reducing Style Bias

Hyeonseob Nam*, HyunJae Lee*, Jongchan Park, Wonjun Yoon, Donggeun Yoo

Conference on Computer Vision and Pattern Recognition (CVPR) 2021, oral


  • Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs

Ju Gang Nam, Minchul Kim, Jongchan Park, Eui Jin Hwang, Jong Hyuk Lee, Jung Hee Hong, Jin Mo Goo, Chang Min Park

European Respiratory Journal (IF 12.339)


  • Learning Visual Context by Comparison

Jongchan Park*, Minchul Kim*, Seil Na, Chang Min Park, and Donggeun Yoo

European Conference for Computer Vision (ECCV) 2020, spotlight (top 5% among submission)


  • Sequential Feature Filtering Classifier

Minseok Seo*, Jaemin Lee*, Jongchan Park, and Dong-Geol Choi

arXiv 2020


  • A Simple and Light-weight Attention Module for Convolutional Neural Networks

Jongchan Park*, Sanghyun Woo*, Joon-Young Lee, and In So Kweon

International Journal of Computer Vision (IJCV)


  • CBAM: Convolutional Block Attention Module

Jongchan Park*, Sanghyun Woo*, Joon-Young Lee, and In So Kweon

European Conference for Computer Vision (ECCV) 2018


  • BAM: Bottleneck Attention Module

Jongchan Park*, Sanghyun Woo*, Joon-Young Lee, and In So Kweon

29TH British Machine Vision Conference (BMVC), oral


  • Distort-and-Recover: Color Enhancement using Deep Reinforcement Learning

Jongchan Park, Joon-Young Lee, Donggeun Yoo, and In So Kweon

Conference on Computer Vision and Pattern Recognition (CVPR) 2018

Work Experiences

  • Lunit Inc. as a research scientist. Mar. 2018 ~

  • Lunit Inc. as a research intern. Oct. 2014 ~ Jul. 2015

  • MyDrives Inc. as a software engineer. Sep 2013 ~ Sep. 2014

Academic Services

  • 2022: CVPR, ECCV reviewer

  • 2021: AAAI, WACV, CVPR, TPAMI reviewer

  • 2020: CVPR, AAAI, BMVC reviewer

  • 2019: CVPR, ICCV, ICCVW (VRMI), MICCAI reviewer

Honors & Awards

  • VisDA 2019 Challenge - SSDA track, Winner

  • 24th Samsung HumanTech Paper Award (w/ BAM: Bottleneck Attention Module), Gold Prize (top 0.5%, $10,000 prize)

  • NVIDIA Deep Learning Contest 2016 (w/ Thermal image enhancement using deep learning algorithm), 1st place

Patents

  • Apparatus for predicting metadata of medical image and method thereof (KR registered, multiple countries pending)

  • Method and apparatus for estimation of tire-road type by using ultrasonic signal (pending)

  • Method and Apparatus for bottleneck attention modules in deep convolutional neural networks (pending)

  • Method and Apparatus for thermal image enhancement using deep learning algorithm (domestic)

  • Method for moving image service of golf, system and computer-readable medium recording the method (domestic)