Joint Pedestrian Detection and Risk-level Prediction with Motion-Representation-by-Detection. - Hirokatsu Kataoka; Teppei Suzuki; Kodai Nakashima; Yutaka Satoh; Yoshimitsu Aoki (ICRA, 2020)

Describing and Localizing Multiple Changes with Transformers. - Yue Qiu 001; Shintaro Yamamoto; Kodai Nakashima; Ryota Suzuki 006; Kenji Iwata; Hirokatsu Kataoka; Yutaka Satoh (ICCV, 2021)

Can Vision Transformers Learn without Natural Images? - Kodai Nakashima; Hirokatsu Kataoka; Asato Matsumoto; Kenji Iwata; Nakamasa Inoue (CoRR, 2021)

Can Vision Transformers Learn without Natural Images? - Kodai Nakashima; Hirokatsu Kataoka; Asato Matsumoto; Kenji Iwata; Nakamasa Inoue; Yutaka Satoh (AAAI, 2022)

Replacing Labeled Real-image Datasets with Auto-generated Contours. - Hirokatsu Kataoka; Ryo Hayamizu; Ryosuke Yamada; Kodai Nakashima; Sora Takashima; Xinyu Zhang; Edgar Josafat Martinez-Noriega; Nakamasa Inoue; Rio Yokota (CVPR, 2022)

Scene Change Captioning in Real Scenarios. - Yue Qiu 001; Kodai Nakashima; Yutaka Satoh; Ryota Suzuki 006; Kenji Iwata; Hirokatsu Kataoka (HCI (35), 2022)

Primitive Geometry Segment Pre-training for 3D Medical Image Segmentation. - Ryu Tadokoro; Ryosuke Yamada; Kodai Nakashima; Ryo Nakamura; Hirokatsu Kataoka (BMVC, 2023)

SegRCDB: Semantic Segmentation via Formula-Driven Supervised Learning. - Risa Shinoda; Ryo Hayamizu; Kodai Nakashima; Nakamasa Inoue; Rio Yokota; Hirokatsu Kataoka (ICCV, 2023)

Does Formula-Driven Supervised Learning Work on Small Datasets? - Kodai Nakashima; Hirokatsu Kataoka; Yutaka Satoh (IEEE Access, 2023)