Sohyun Lee

Integrated M.S. & Ph.D. student in the Computer Vision Lab at POSTECH.

SohyunLee.png

Room#302, B2,

Chungam-Ro 77, POSTECH,

Pohang, Gyeongbuk,

South Korea 37673

I am a graduate student in the Graduate School of Artificial Intelligence integrated M.S. & Ph.D. program at POSTECH. I am a member of the Computer Vision Lab at POSTECH, advised by Prof. Suha Kwak. Previously, I completed my B.S. in Mechanical Engineering at POSTECH.

My research interests lie in computer vision and deep learning. I’ve worked on the robust recognition in adverse visual conditions, domain adaptation, and generalization.

If you are interested in my research projects, please feel free to contact me by clicking one of the icons below.

News

Nov 7, 2022 :trophy: Three papers got honored to be the winners at the Qualcomm Innovation Fellowship 2022.
Jul 4, 2022 📝 A paper on active domain adaptation is accepted to ECCV 2022.
Jun 21, 2022 :trophy: Our paper on foggy scene segmentation is nominated as a best paper finalist in CVPR 2022.
Mar 3, 2022 📝 Two papers (including one best paper finalist) are accepted to CVPR 2022.
Dec 1, 2020 :trophy: I won the POSTECH Creative Self-Research Scholarship.

Education

Sep, 2020 - Present Pohang University of Science and Technology (POSTECH), Pohang, South Korea
Integrated M.S. & Ph.D. Student in Artificial Intelligence
Advisor: Prof. Suha Kwak.
Mar, 2015 - Aug, 2020 Pohang University of Science and Technology (POSTECH), Pohang, South Korea
B.S in Mechanical Engineering
Advisor: Prof. Junsuk Rho.

Publications

  1. Combating Label Distribution Shift for Active Domain Adaptation
    Sehyun Hwang,  Sohyun Lee, Sungyeon Kim, Jungseul Ok, and Suha Kwak
    European Conference on Computer Vision (ECCV), 2022
    Qualcomm Innovation Fellowship 2022
  2. FIFO: Learning Fog-invariant Features for Foggy Scene Segmentation
    Sohyun Lee, Taeyoung Son, and Suha Kwak
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
    (Oral Presentation, Best Paper Finalist)
    Invited paper talk at V4AS Workshop @ CVPR 2022
    Qualcomm Innovation Fellowship 2022
  3. Style Neophile: Constantly Seeking Novel Styles for Domain Generalization
    Juwon Kang,  Sohyun Lee, Namyup Kim, and Suha Kwak
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
    Qualcomm Innovation Fellowship 2022

Professional Services

Reviewer
  • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022-2023
  • IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023
  • Asian Conference on Computer Vision (ACCV), 2022
  • European Conference on Computer Vision (ECCV), 2022

Honors and Awards

Qualcomm Innovation Fellowship South Korea Winner, 2022
  • FIFO: Learning Fog-invariant Features for Foggy Scene Segmentation (CVPR 2022, Best Paper Finalist)
  • Style Neophile: Constantly Seeking Novel Styles for Domain Generalization (CVPR 2022)
  • Combating Label Distribution Shift for Active Domain Adaptation (ECCV 2022)
CVPR Best Paper Finalist, 2022
  • Awarded to Top 0.4% (33 of 8161 papers)
  • FIFO: Learning Fog-invariant Features for Foggy Scene Segmentation (CVPR 2022, Best Paper Finalist)
Gold Prize at IPIU Best Paper Award, 2022
  • Research Topic: Active Domain Adaptation
POSTECH Creative Self-Research Scholarship, 2020
  • Research Topic: Unsupervised domain adaptation for semantic segmentation