| Pre-training without natural images H Kataoka, K Okayasu, A Matsumoto, E Yamagata, R Yamada, N Inoue, ... Proceedings of the Asian Conference on Computer Vision, 2020 | 131 | 2020 |
| Point cloud pre-training with natural 3d structures R Yamada, H Kataoka, N Chiba, Y Domae, T Ogata Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 38 | 2022 |
| Replacing labeled real-image datasets with auto-generated contours H Kataoka, R Hayamizu, R Yamada, K Nakashima, S Takashima, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 34 | 2022 |
| Formula-driven supervised learning with recursive tiling patterns H Kataoka, A Matsumoto, R Yamada, Y Satoh, E Yamagata, N Inoue Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 16 | 2021 |
| Age should not matter: Towards more accurate pedestrian detection via self-training S Kogure, K Watabe, R Yamada, Y Aoki, A Nakamura, H Kataoka Computer Sciences & Mathematics Forum 3 (1), 11, 2022 | 8 | 2022 |
| 3d change localization and captioning from dynamic scans of indoor scenes Y Qiu, S Yamamoto, R Yamada, R Suzuki, H Kataoka, K Iwata, Y Satoh Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 7 | 2023 |
| Mv-fractaldb: Formula-driven supervised learning for multi-view image recognition R Yamada, R Takahashi, R Suzuki, A Nakamura, Y Yoshiyasu, R Sagawa, ... 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 7 | 2021 |
| Primitive Geometry Segment Pre-training for 3D Medical Image Segmentation R Tadokoro, R Yamada, K Nakashima, R Nakamura, H Kataoka arXiv preprint arXiv:2401.03665, 2024 | 5 | 2024 |
| Pre-training auto-generated volumetric shapes for 3d medical image segmentation R Tadokoro, R Yamada, H Kataoka Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4 | 2023 |
| Pre-training without natural images K Hirokatsu, M Asato, Y Eisuke, Y Ryosuke, I Nakamasa, A Nakamura, ... International Journal of Computer Vision 130 (4), 990-1007, 2022 | 3 | 2022 |
| フラクタル幾何学に基づいた多視点画像自動生成によるデータセット拡張手法 山田亮佑， 鈴木亮太， 中村明生， 片岡裕雄 精密工学会誌 87 (12), 1013-1019, 2021 | 1 | 2021 |
| Formula-Supervised Visual-Geometric Pre-training R Yamada, K Hara, H Kataoka, K Makihara, N Inoue, R Yokota, Y Satoh European Conference on Computer Vision, 57-74, 2025 | | 2025 |
| Rethinking Image Super-Resolution from Training Data Perspectives G Ohtani, R Tadokoro, R Yamada, YM Asano, I Laina, C Rupprecht, ... European Conference on Computer Vision, 19-36, 2025 | | 2025 |
| Masked Structural Point Cloud Modeling to Learning 3D Representation R Yamada, R Tadokoro, Y Qiu, H Kataoka, Y Satoh IEEE Access, 2024 | | 2024 |
| Scaling Backwards: Minimal Synthetic Pre-training? R Nakamura, R Tadokoro, R Yamada, YM Asano, I Laina, C Rupprecht, ... arXiv preprint arXiv:2408.00677, 2024 | | 2024 |
| Exploring the Potential of Neural Dataset Search R Yamada, R Shinoda, H Kataoka Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | | 2023 |
| Multi-view Fractal DataBase: フラクタル幾何学に基づく多視点画像データセット生成 山田亮佑， 中村明生， 鈴木亮太， 片岡裕雄 画像ラボ/画像ラボ編集委員会 編 33 (1), 21-28, 2022 | | 2022 |
| 会議報告: IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR 2021) 片岡裕雄， 原健翔， 鈴木亮太， 福原吉博， 綱島秀樹， 中嶋航大， 中村凌， ... 人工知能 36 (6), 798-804, 2021 | | 2021 |
| 自然の形成原理による CNN の学習 片岡裕雄， 山田亮佑， 松本晟人 Medical Imaging Technology 39 (3), 117-123, 2021 | | 2021 |
| フラクタル幾何学に基づく大規模事前学習データベース自動構築と三次元物体認識への適用 山田亮佑， 岡安寿繁， 中村明生， 片岡裕雄 精密工学会誌 87 (4), 374-379, 2021 | | 2021 |
Hirokatsu KataokaAIST / University of OxfordBestätigte E-Mail-Adresse bei aist.go.jp
Hirokatsu KataokaAIST / University of OxfordBestätigte E-Mail-Adresse bei aist.go.jp