Profile
Bio.
Hirokatsu Kataoka received his Ph.D. in engineering from Keio University in 2014. His research experience includes visiting scientist at Technical University of Munich (TUM) and JSPS Fellow (PD) at the University of Tokyo. Currently, he is a Chief Senior Researcher at National Institute of Advanced Industrial Science and Technology (AIST). He also leads the cvpaper.challenge which conducts comprehensive survey and collaborative research in the field of computer vision and related academic fields. He has contributed to develop a strong baseline for video recognition in spatiotemporal 3D ResNets, and establish a novel learning strategy in Formula-Driven Supervised Learning (FDSL). He has received ACCV 2020 Best Paper Honorable Mention Award, AIST 2019 Best Paper Award, and ECCV 2016 Workshop Brave New Idea, and was featured in MIT Technology Review.
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Latest Professional Experience
Chief Senior Researcher, National Institute of Advanced Industrial Science and Technology (AIST)
(April 2023 - Present) -
Latest Education
Ph.D. in Engineering, Keio University
(April 2011 - March 2014)
What’s new?
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Sep 27, 2023
Two papers (DataComp, Document Dataset) have been accepted to ICCV 2023 Workshop.
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Sep 14, 2023
Our paper (FDSL in 3D medical image segmentation) has been accepted to BMVC 2023 Oral.
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Sep 01, 2023
3D-ResNet is listed as Most Cited Paper within 5 Years in CVPR (47th out of 8800+ papers) [Link]
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Aug 04, 2023
Our paper (Diffusion-based Texture Synthesis) has been accepted to SIGGRAPH Asia 2023.
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Jul 14, 2023
Three papers (FDSL, Adversarial Examples) have been accepted to ICCV 2023.
Projects
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cvpaper.challenge
We are finding a collaborator to read/write a sophisticated paper!
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Pre-training without Natural Images
We would like to replace Supervised/Self-supervised Learning!
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Alleviating Over-segmentation Errors by Detecting Action Boundaries
Detecting action boundary significantly improves segmentation performance.
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View-agnostic Image Rendering
We generate novel-view images.
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Scene Change Captioning
We can describe a change area in a real environment.
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Weakly Supervised Person Dataset (WSPD)
Our weak-supervision surpassed a supervised pre-training.
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Neural Joking Machine: Humorous image captioning
Now we are joking!
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Drive Video Analysis for the Detection of Traffic Near-Miss Incidents
We have collected large-scale traffic near-miss incident database!
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Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
3D Conv is ready to be used various video applications!
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Dynamic Fashion Cultures
Now we can start a world-wide fashion analysis!
Selected Papers
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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)
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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)
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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)
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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.
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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)
