Hongje Seong

hongjeseong.jpg

📧 hjseong [at] yonsei.ac.kr

📍 C607, 3rd Eng. Bldg, 50 Yonsei-ro, Seodaemun-gu, Seoul, Korea, 03722

CV | Google Scholar | Github

Ph. D. Candidate, Yonsei University.

I am a Ph.D. student advised by Professor Euntai Kim, at Electrical and Electronic Engineering, Yonsei University. I earned my B.S. degree in Electrical and Electronic Engineering from Yonsei University in 2018. I was a research intern at Adobe Research (San Jose, CA) in 2021. During my internship, I worked at the Creative Intelligence Lab with Joon-Young Lee, Seoung Wug Oh, and Brian Price as my mentors.

I am broadly interested in computer vision. Specifically, my research interests include

  • Image / Video Segmentation
  • Image / Video Matting
  • Image / Video Recognition
  • Domain Adaptation / Generalization
  • Image Retrieval / Place Recognition
but not limited to.

selected publications

  1. One-Trimap Video Matting
    European Conference on Computer Vision (ECCV), Oct, 2022
    (Acceptance: 1650/5803 ≈ 28.4%)
  2. Video Object Segmentation using Kernelized Memory Network with Multiple Kernels
    Hongje Seong, Junhyuk Hyun, and Euntai Kim
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 (Accepted)
    (IF: 24.314 in JCR2021)
  3. Indoor Place Category Recognition for a Cleaning Robot by Fusing a Probabilistic Approach and Deep Learning
    Soowook Choe*,  Hongje Seong*, and Euntai Kim
    IEEE Transactions on Cybernetics (TCYB), Aug, 2022
    (IF: 19.118 in JCR2021, * indicates equal contribution)
  4. Correlation Verification for Image Retrieval
    Seongwon LeeHongje SeongSuhyeon Lee, and Euntai Kim
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun, 2022
    (Acceptance: 342/8161 ≈ 4.2%)
      Oral Presentation  
  5. WildNet: Learning Domain Generalized Semantic Segmentation from the Wild
    Suhyeon LeeHongje SeongSeongwon Lee, and Euntai Kim
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun, 2022
    (Acceptance: 2067/8161 ≈ 25.3%)
  6. Iteratively Selecting an Easy Reference Frame Makes Unsupervised Video Object Segmentation Easier
    Youngjo Lee,  Hongje Seong, and Euntai Kim
    AAAI Conference on Artificial Intelligence (AAAI), Feb, 2022
    (Acceptance: 1349/9020 ≈ 15.0%)
  7. Graph-Based Point Tracker for 3D Object Tracking in Point Clouds
    Minseong Park,  Hongje Seong, Wonje Jang, and Euntai Kim
    AAAI Conference on Artificial Intelligence (AAAI), Feb, 2022
    (Acceptance: 1349/9020 ≈ 15.0%)
  8. Adjacent Feature Propagation Network (AFPNet) for Real-Time Semantic Segmentation
    Junhyuk Hyun,  Hongje Seong, Sangki Kim, and Euntai Kim
    IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC), 2021 (Accepted)
    (IF: 13.451 in JCR2020)
  9. Hierarchical Memory Matching Network for Video Object Segmentation
    IEEE/CVF International Conference on Computer Vision (ICCV), Oct, 2021
    (Acceptance: 1617/6236 ≈ 25.9%)
  10. Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer
    Suhyeon Lee, Junhyuk Hyun,  Hongje Seong, and Euntai Kim
    AAAI Conference on Artificial Intelligence (AAAI), Feb, 2021
    (Acceptance: 1692/7911 ≈ 21.4%)
  11. Kernelized Memory Network for Video Object Segmentation
    Hongje Seong, Junhyuk Hyun, and Euntai Kim
    European Conference on Computer Vision (ECCV), Aug, 2020
    (Acceptance: 1361/5025 ≈ 27.1%)
      3rd Place Award in DAVIS20 Challenge (CVPRW-DAVIS 2020)