Top-Rank＝ indicates top-ranked conference/journal in Google Scholar Metrics.
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Takumi Fukuzawa, Kensho Hara, Hirokatsu Kataoka, Toru Tamaki, “Can masking background and object reduce static bias for zero-shot action recognition?,” International Conference on MultiMedia Modeling (MMM), 2025.
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Kenji Doi, Shutaro Okada, Ryota Yoshihashi, Hirokatsu Kataoka, “Real-SRGD: Enhancing Real-World Image Super-Resolution with Classifier-Free Guided Diffusion,” Asian Conference on Computer Vision (ACCV), 2024.
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Ryota Yoshihashi, Yuya Otsuka, Kenji Doi, Tomohiro Tanaka, Hirokatsu Kataoka, “Exploring Limits of Diffusion-Synthetic Training with Weakly Supervised Semantic Segmentation,” Asian Conference on Computer Vision (ACCV), 2024.
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Ryosuke Yamada,Ryu Tadokoro,Yue Qiu,Hirokatsu Kataoka,Yutaka Satoh, “Masked Structural Point Cloud Modeling for Learning 3D Representation,” IEEE Access, 2024.
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Fumiya Matsuzawa, Yue Qiu, Yanjun Sun, Kenji Iwata, Hirokatsu Kataoka, Yutaka Satoh, “Subtle-Diff: A Dataset for Precise Recognition of Subtle Differences among Visually Similar Objects,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024.
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Shinichi Mae, Ryosuke Yamada, Hirokatsu Kataoka, “Keeping Segment Mask Quality with Self-generated Masks,” ECCV 2024 Workshop on Darkside of GenAIs and Beyond, 2024.
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Top-Rank
Ryosuke Yamada, Kensho Hara, Hirokatsu Kataoka, Koshi Makihara, Nakamasa Inoue, Rio Yokota, Yutaka Satoh, “Formula-Supervised Visual-Geometric Pre-training,” European Conference on Computer Vision (ECCV), 2024.
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Go Ohtani, Ryu Tadokoro, Ryosuke Yamada, Yuki M Asano, Iro Laina, Christian Rupprecht, Nakamasa Inoue, Rio Yokota, Hirokatsu Kataoka, Yoshimitsu Aoki, “Rethinking Image Super Resolution from Training Data Perspectives,” European Conference on Computer Vision (ECCV), 2024.
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Ryo Nakamura, Ryu Tadokoro, Ryosuke Yamada, Yuki M. Asano, Iro Laina, Christian Rupprecht, Nakamasa Inoue, Rio Yokota, Hirokatsu Kataoka, “Scaling Backwards: Minimal Synthetic Pretraining?,” European Conference on Computer Vision (ECCV), 2024.
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Erika Mori, Yue Qiu, Hirokatsu Kataoka, Yoshimitsu Aoki, “Advancing AI’s Social Intelligence: Combining Commonsense Reasoning with Visual Perception,” ECCV 2024 WiCV Workshop.
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Shun Iwase, Eisaku Maeda, Nakamasa Inoue, Hirokatsu Kataoka, Ryo Nakamura, Rio Yokota, Shuya Takahashi, “On the Relationship Between Double Descent of CNNs and Shape/Texture Bias Under Learning Process,” ICPR 2024.
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Ryosuke Yamada, Ryosuke Takahashi, Go Ohtani, Erika Mori, Hirokatsu Kataoka, Yoshimitsu Aoki, “Is ImageNet Pre-training Fiar in Image Recognition?,” CVPR Workshop on Responsible Data, 2024.
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Ryo Hayamizu, Shota Nakamura, Sora Takashima, Hirokatsu Kataoka, Ikuro Sato, Nakamasa Inoue, Rio Yokota, “SIFTer: Self-improving Synthetic Datasets for Pre-training Classification Models,” CVPR Workshop on Synthetic Dataset for Computer Vision, 2024.
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Top-Rank
Peifei Zhu, Tsubasa Takahashi, Hirokatsu Kataoka, Watermark-embedded Adversarial Examples for Copyright Protection against Diffusion Models, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
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Yuichi Iwasaki, Hiroko Arai, Akihiro Tamada, Hirokatsu Kataoka, “Japanese mayfly family classification with a vision transformer model”, EcoEvoRxiv, 2024.
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Yanjun Sun, Yue Qiu, Yoshimitsu Aoki, Hirokatsu Kataoka, “Guided by the Way: The Role of On-the-route Objects and Scene Text in Enhancing Outdoor Navigation”, ICRA 2024.
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Ryo Nakamura, Ryu Tadokoro, Eisuke Yamagata, Yusuke Kondo, Kensho Hara, Hirokatsu Kataoka, Nakamasa Inoue, “Pseudo-outlier synthesis using q-Gaussian distributions for out-of-distribution detection”, ICASSP 2024.
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Yuchi Ishikawa, Masayoshi Kondo, Hirokatsu Kataoka, “Learnable Cube-Based Video Encryption for Privacy-Preserving Action Recognition”, WACV, 2024.
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Guoqing Hao, Satoshi Iizuka, Kensho Hara, Edgar Simo-Serra, Hirokatsu Kataoka, Kazuhiro Fukui, “Diffusion-based Texture Rectification and Synthesis”, SIGGRAPH Asia, 2023.
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Yamato Okamoto, Osada Genki, Iu Yahiro, Rintaro Hasegawa, Peifei Zhu, Hirokatsu Kataoka, “Image Generation and Learning Strategy for Deep Document Forgery Detection” arXiv pre-print:2311.03650, 2023.