Hirokatsu KATAOKA

Hirokatsu KATAOKA, Ph.D.

Chief Senior Researcher, AIST, Japan.

Profile

Bio.

1. Chief Senior Researcher, AIST/ 2. Academic Visitor, Visual Geometry Group (VGG), University of Oxford / 3. Visiting Associate Professor, Keio University / 4. Adjunct Associate Professor, Tokyo Denki University / 5. Research Advisor, SB Intuitions / 6. Principal Investigator, cvpaper.challenge / 7. Principal Investigator, LIMIT.Lab

 

He proposed 3D ResNets as a baseline spatiotemporal model, which became one of the top 0.5% most-cited papers at CVPR over a five-year period. He also introduced Formula-Driven Supervised Learning (FDSL), a synthetic pre-training method without real images and human labor, which earned an ACCV 2020 Best Paper Honorable Mention Award. He received the Fujiwara Prize in 2014 (valedictorian equivalent) from Keio University, participated in the ECCV 2016 Workshop “Brave New Idea,” and won the AIST Best Paper Award in 2019 and 2022, was also a BMVC 2023 Best Industry Paper Finalist. He has served as primary organizer of the LIMIT Workshops at ICCV 2023, CVPR 2024, and ICCV 2025, as Area Chair for CVPR 2024 and 2025, and will serve as an IEEE TPAMI Associate Editor beginning in 2025. His work has been featured in MIT Technology Review.

  • Latest Professional Experience

    Visiting Researcher, Visual Geometry Group, University of Oxford (Oxford VGG)
    (September, 2024 - )

  • Latest Education

    Ph.D. in Engineering, Keio University
    (April 2011 - March 2014)

What’s new?

  • Jun 09, 2025

    We’ve established LIMIT.Lab [Link] a collaboration hub for building multimodal AI models under limited resources, covering images, videos, 3D, and text, when any resource (e.g., compute, data, or labels) is constrained.

  • Mar 06, 2025

    Our FDSL pre-training for microfossil radiolarians has been accepted to Scientific Reports [Link], and published from AIST press release [Link].

  • Dec 21, 2024

    Our paper (Audio FDSL) has been accepted to ICASSP 2025.

  • Sep 27, 2024

    Two papers (Weakly Supervised Segmentation, Real-world Super Resolution) have been accepted to ACCV 2024.

  • Jul 01, 2024

    Three papers (Super Resolution, Multimodal & Limited Pre-training) have been accepted to ECCV 2024.

Projects

Selected Papers

  • Selected Papers Top-Rank

    Hirokatsu Kataoka, Ryo Hayamizu, Ryosuke Yamada, Kodai Nakashima, Sora Takashima, Xinyu Zhang, Edgar Josafat Martinez-Noriega, Nakamasa Inoue, Rio Yokota, “Replacing Labeled Real-Image Datasets with Auto-Generated Contours”, IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), 2022.(Acceptance rate: 25.3%; 1st place in Computer Vision at Google Scholar Metrics)

  • Selected Papers Top-Rank

    Ryosuke Yamada*, Hirokatsu Kataoka*, Naoya Chiba, Yukiyasu Domae Tetsuya Ogata, “Point Cloud Pre-training with Natural 3D Structures”, IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), 2022.(Acceptance rate: 25.3%; 1st place in Computer Vision at Google Scholar Metrics; * indicates equal contribution)

  • Selected Papers Top-Rank

    Hirokatsu Kataoka, Kazushige Okayasu, Asato Matsumoto, Eisuke Yamagata, Ryosuke Yamada, Nakamasa Inoue, Akio Nakamura, Yutaka Satoh, “Pre-training without Natural Images”, International Journal of Computer Vision (IJCV), 2022. (IF: 7.410)

  • Selected Papers Top-Rank

    Kodai Nakashima, Hirokatsu Kataoka, Asato Matsumoto, Kenji Iwata, Nakamasa Inoue, Yutaka Satoh, “Can Vision Transformers Learn without Natural Images?,” AAAI Conference on Artificial Intelligence (AAAI), 2022.

  • Selected Papers Top-Rank

    Hirokatsu Kataoka, Kazushige Okayasu, Asato Matsumoto, Eisuke Yamagata, Ryosuke Yamada, Nakamasa Inoue, Akio Nakamura, Yutaka Satoh, “Pre-training without Natural Images”, Asian Conference on Computer Vision (ACCV), 2020. (Best Paper Honorable Mention Award; Oral Presentation; 3 Strong Accepts)

Research Team

21 Total

RA(Ph.D.)

RA(Master)

Intern

Affiliation