| 2023 | WACV | Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data Augmentation. | Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa |
| 2022 | AAAI | Self-Labeling Framework for Novel Category Discovery over Domains. | Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa |
| 2021 | CVPR | Generalized Domain Adaptation. | Yu Mitsuzumi, Go Irie, Daiki Ikami, Takashi Shibata |
| 2021 | IJCAI | Learning with Selective Forgetting. | Takashi Shibata, Go Irie, Daiki Ikami, Yu Mitsuzumi |
| 2021 | WACV | Constrained Weight Optimization for Learning without Activation Normalization. | Daiki Ikami, Go Irie, Takashi Shibata |
| 2020 | ACCV | Cascaded Transposed Long-Range Convolutions for Monocular Depth Estimation. | Go Irie, Daiki Ikami, Takahito Kawanishi, Kunio Kashino |
| 2020 | ECCV | Multi-task Curriculum Framework for Open-Set Semi-supervised Learning. | Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa |
| 2020 | ICPR | The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals. | Takumi Kawashima, Qing Yu, Akari Asai, Daiki Ikami, Kiyoharu Aizawa |
| 2019 | CVPR | Multi-Task Learning based on Separable Formulation of Depth Estimation and its Uncertainty. | Akari Asai, Daiki Ikami, Kiyoharu Aizawa |
| 2019 | ISM | Synthesis of Screentone Patterns of Manga Characters. | Koki Tsubota, Daiki Ikami, Kiyoharu Aizawa |
| 2018 | CVPR | Local and Global Optimization Techniques in Graph-Based Clustering. | Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa |
| 2018 | CVPR | Fast and Robust Estimation for Unit-Norm Constrained Linear Fitting Problems. | Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa |
| 2018 | CVPR | Joint Optimization Framework for Learning With Noisy Labels. | Daiki Tanaka, Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa |
| 2017 | CVPR | Residual Expansion Algorithm: Fast and Effective Optimization for Nonconvex Least Squares Problems. | Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa |