Jun-Hyuk Kim

Ph.D. student

junhyuk.kim@yonsei.ac.kr

I am a PhD student at the Multimedia Computing and Machine Learning (MCML) Group of Yonsei University under the supervision of Prof. Jong-Seok Lee. I received the B.S. degree in the School of Integrated Technology from Yonsei University, South Korea, in 2015. My research interests include low-level computer vision and deep learning.


Publications

  • Preprints
  • Lightweight and efficient image super-resolution with block state-based recursive network
    J.-H. Choi, J.-H. Kim, M. Cheon, J.-S. Lee
    arXiv:1811.12546, November 2018
    arXiv / GitHub

  • Journals
  • MAMNet: Multi-path adaptive modulation network for image super-resolution
    J.-H. Kim, J.-H. Choi, M. Cheon, J.-S. Lee
    Neurocomputing, accepted
    arXiv / GitHub

    Deep learning-based image super-resolution considering quantitative and perceptual quality
    J.-H. Choi, J.-H. Kim, M. Cheon, J.-S. Lee
    Neurocomputing, accepted
    arXiv / GitHub

    Prediction of car design perception using EEG and gaze patterns
    S.-E. Moon, J.-H. Kim, S.-W. Kim, J.-S. Lee
    IEEE Transactions on Affective Computing, accepted
    Detail

  • Conferences
  • Efficient deep learning-based lossy image compression via asymmetric autoencoder and pruning
    J.-H. Kim, J.-H. Choi, J. Chang, J.-S. Lee
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020

    SRZoo: An integrated repository for super-resolution using deep learning
    J.-H. Choi, J.-H. Kim, J.-S. Lee
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020
    GitHub

    Evaluating robustness of deep image super-resolution against adversarial attacks
    J.-H. Choi, H. Zhang, J.-H. Kim, C.-J. Hsieh, J.-S. Lee
    IEEE International Conference on Computer Vision (ICCV), pp. 303-311, October 2019
    Detail / arXiv

    Deep learning-based super-resolution for digital comics
    J.-H. Kim, J.-H. Choi, C.-H. Seo, J. Chang, J.-S. Lee
    SIGGRAPH Asia 2018 Posters, Article 19, December 2018
    Detail

    Generative adversarial network-based image super-resolution using perceptual content losses
    M. Cheon, J.-H. Kim, J.-H. Choi, J.-S. Lee
    European Conference on Computer Vision (ECCV) Workshops, pp. 51-62, September 2018
    Detail / arXiv / GitHub

    Deep residual network with enhanced upscaling module for super-resolution
    J.-H. Kim, J.-S. Lee
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 913-921, Jun. 2018
    Detail / GitHub

    NTIRE 2018 challenge on single image super-resolution: methods and results
    R. Timofte et al. (including J.-H. Kim)
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 965-976, Jun. 2018
    Detail

    Assessing product design using photos and real products
    S.-E. Moon, J.-H. Kim, S.-W. Kim, J.-S. Lee
    ACM Conf. Human Factors in Computing Systems (CHI), Extended Abstract, pp. 1100-1107, May 2017
    Detail

    Travel photo album summarization based on aesthetic quality, interestingness, and memorableness
    J.-H. Kim, J.-S. Lee
    APSIPA Annual Summit and Conference, Dec. 2016
    Detail

    Awards

    2nd Place (Region 1)
    Yonsei-MCML team
    Super-Resolution Challenge on Perceptual Image Restoration and Manipulation (PIRM), in conjunction with ECCV, September 2018
    Leaderboard / GitHub

    2nd Place (Region 2)
    Yonsei-MCML team
    Super-Resolution Challenge on Perceptual Image Restoration and Manipulation (PIRM), in conjunction with ECCV, September 2018
    Leaderboard / GitHub