I am a MS student advised by Professor In So Kweon, at Future Vehicle Engineering, KAIST.

My research interests currently lie in computer vision. Specifically, I pursue the goal to build domain adaptive recognition in computer vision, which handles data hungry problem in deep learning. My research topics include Unsupervised domain adaptation / Self-supervised learning.

Contact

  • dlsrbgg33 [at] kaist.ac.kr

    dlsrbgg33 [at] gmail.com

  • Bldg N1, Rm 211, 291 Daehak-ro, Yuseong-gu, Daejeon, Korea, 34141

Education

  • BS in Future Vehicle Engineering, 2019

    HYU, Korea

Research Experiences

  • Korea University, Seoul, Korea
    Sep 2018 - Dec 2018

    Research Intern, Data and Visual Analytics Lab.
  • Hanyang University, Seoul, Korea
    Jul 2018 - Aug 2018

    Research Assistant, Automotive Control and Electronics Laboratory.
  • Samsung Electronics., Hwasung,
    Jan 2018 - Mar 2018

    Research Intern, Semi-conductor Test group.

Publications

  • Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation

    Kwanyong Park, Sanghyun Woo, Inkyu Shin, Inso Kweon

    NeurIPS 2020

    [ Paper ]

  • Two-phase Pseudo Label Densification for Self-training based Domain Adaptation

    Inkyu Shin, Sanghyun Woo, Fei Pan, Inso Kweon

    ECCV 2020

    *Also presented at CVPR 2020 Workshop(VL3)

    [ Paper ]

  • Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision

    Fei Pan, Inkyu Shin, Francois Rameau, Seokju Lee, Inso Kweon

    CVPR 2020 [Oral]

    [ Project page | Paper | Code ]

  • Image-to-image translation via group-wise deep whitening-and-coloring transformation

    Wongwoong Cho, Sungha Choi, David Keetae Park, Inkyu Shin, Jaegul Choo

    CVPR 2019 [Oral]

    [ Paper | Code ]

Activities

Teaching Assistant

  • Perception for autonomous-driving

Talks

  • Naver Labs
  • Topic: Unsupervised Domain Adaptation