Kazuki Kozuka Kazuki Kozuka

Kazuki Kozuka

Ph.D. in Computer Science
Technology Division

He specializes in basic and applied research of computer vision and image recognition. He joined Stanford AI Laboratory as a visiting researcher from Apr.2016 to Mar.2019 and conducted his research among world class researchers. Through such experiences, now he focuses on innovation and R&D beyond organizational boundaries.
Recently he leads CAMP workshop in conjunction with ECCV2020.
CAMP workshop: https://camp-workshop.stanford.edu/

*The department is where the interviewee belonged to at that time
(2016.4-2019.3 Joined SAIL as a visiting researcher)

Publications

  • ECCV2022 Workshop AV4D: Visual Learning of Sounds in Spaces

    Invisible-to-Visible: Privacy-Aware Human Segmentation using Airborne Ultrasound via Collaborative Learning Probabilistic U-Net

    Risako Tanigawa, Yasunori Ishii, Kazuki Kozuka, Takayoshi Yamashita
    Link: https://arxiv.org/abs/2205.05293

  • arXiv:2204.07280

    Invisible-to-Visible: Privacy-Aware Human Instance Segmentation using Airborne Ultrasound via Collaborative Learning Variational Autoencoder

    Risako Tanigawa, Yasunori Ishii, Kazuki Kozuka, Takayoshi Yamashita
    Link: https://arxiv.org/abs/2204.07280

  • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021

    Home Action Genome: Cooperative Compositional Action Understanding

    Nishant Rai, Haofeng Chen, Jingwei Ji, Rishi Desai, Kazuki Kozuka, Shun Ishizaka, Ehsan Adeli, Juan Carlos Niebles
    Link: https://arxiv.org/abs/2105.05226

  • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021

    AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implicit Differentiation

    Denis Gudovskiy,Luca Rigazio, Shun Ishizaka,Kazuki Kozuka, Sotaro Tsukizawa
    Link: https://arxiv.org/abs/2103.05863

  • International Conference on Computer Vision Theory and Applications (VISAPP) 2020

    Simultaneous Visual Context-aware Path Prediction

    Haruka Iesaki, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, Yasunori Ishii, Kazuki Kozuka, Ryota Fujimura
    Link: https://www.scitepress.org/Link.aspx?doi=10.5220/0008921307410748

  • ICCV 2017 Workshop on Computer Vision for Road Scene Understanding and Autonomous Driving

    Risky Region Localization With Point Supervision

    Kazuki Kozuka, Juan Carlos Niebles
    Link: http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w3/Kozuka_Risky_Region_Localization_ICCV_2017_paper.pdf

  • International Journal of Machine Learning and Computing, Vol. 6, No. 1

    Whole Layers Transfer Learning of Deep Neural Networks for a Small Scale Dataset

    Yoshihide Sawada, Kazuki Kozuka
    Link: http://www.ijmlc.org/vol6/566-L0077.pdf

  • IEEE Engineering in Medicine and Biology Society (EMBC) 2015

    Development of Automatic Database Registration and Similar-Case Retrieval for Diffuse Lung Diseases by Texture Analysis of Whole-Lung CT Volume

    Kazuki Kozuka, Takata, Kazutoyo, Kondo, Kenji, Kyohei Karasawa, Yasushi Hirano, Shoji Kido

  • IEEE Engineering in Medicine and Biology Society (EMBC) 2015

    Estimation of Knee Extensor Strength Using Wearable Sensors

    Yoshikuni Sato, Toru Nakada, Kazuki Kozuka, Masaki Kiyono, Tadayoshi Nonoyama, Masafumi Kubota, Yusuke Koie, Masaki Yasutake, Osamu Yamamura

  • IEEE Engineering in Medicine and Biology Society (EMBC) 2015

    Prediction of PeakVO2 from Walking Energy Cost Index for the Elderly

    Toru Nakada, Yoshikuni Sato, Kazuki Kozuka, Masaki Kiyono, Tadayoshi Nonoyama, Masafumi Kubota, Yusuke Koie, Masaki Yasutake, Osamu Yamamura

  • 29th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS) 2015

    Development of lung CT image retrieval technology using distance metric learning by image findings

    Kazuki Kozuka, Kazutoyo Takata, Kenji Kondo, Masaki Kiyono, Masato Tanaka, Toyohiko Sakai, Hirohiko Kimura

  • IAPR Machine Vision And Application Organization (MVA) 2015

    Transfer Learning Method using Multi-Prediction Deep Boltzmann Machines for a small scale dataset

    Yoshihide Sawada, Kazuki Kozuka
    Link: http://www.mva-org.jp/Proceedings/2015USB/papers/05-21.pdf