| Maximum classifier discrepancy for unsupervised domain adaptation K Saito, K Watanabe, Y Ushiku, T Harada Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 2373 | 2018 |
| Neural 3d mesh renderer H Kato, Y Ushiku, T Harada Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 1205 | 2018 |
| Strong-weak distribution alignment for adaptive object detection K Saito, Y Ushiku, T Harada, K Saenko Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 791 | 2019 |
| Asymmetric tri-training for unsupervised domain adaptation K Saito, Y Ushiku, T Harada International conference on machine learning, 2988-2997, 2017 | 734 | 2017 |
| Open set domain adaptation by backpropagation K Saito, S Yamamoto, Y Ushiku, T Harada Proceedings of the European conference on computer vision (ECCV), 153-168, 2018 | 627 | 2018 |
| MFNet: Towards real-time semantic segmentation for autonomous vehicles with multi-spectral scenes Q Ha, K Watanabe, T Karasawa, Y Ushiku, T Harada 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 518 | 2017 |
| Open x-embodiment: Robotic learning datasets and rt-x models A O'Neill, A Rehman, A Gupta, A Maddukuri, A Gupta, A Padalkar, A Lee, ... arXiv preprint arXiv:2310.08864, 2023 | 362* | 2023 |
| Domain generalization using a mixture of multiple latent domains T Matsuura, T Harada Proceedings of the AAAI conference on artificial intelligence 34 (07), 11749 …, 2020 | 344 | 2020 |
| Adversarial dropout regularization K Saito, Y Ushiku, T Harada, K Saenko arXiv preprint arXiv:1711.01575, 2017 | 340 | 2017 |
| Learning from between-class examples for deep sound recognition Y Tokozume, Y Ushiku, T Harada arXiv preprint arXiv:1711.10282, 2017 | 314 | 2017 |
| Between-class learning for image classification Y Tokozume, Y Ushiku, T Harada Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 264 | 2018 |
| Learning environmental sounds with end-to-end convolutional neural network Y Tokozume, T Harada 2017 IEEE international conference on acoustics, speech and signal …, 2017 | 250 | 2017 |
| Image generation from small datasets via batch statistics adaptation A Noguchi, T Harada Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 230 | 2019 |
| Neural articulated radiance field A Noguchi, X Sun, S Lin, T Harada Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 220 | 2021 |
| Multispectral object detection for autonomous vehicles K Takumi, K Watanabe, Q Ha, A Tejero-De-Pablos, Y Ushiku, T Harada Proceedings of the on Thematic Workshops of ACM Multimedia 2017, 35-43, 2017 | 182 | 2017 |
| Hyperbolic neural networks++ R Shimizu, Y Mukuta, T Harada arXiv preprint arXiv:2006.08210, 2020 | 155 | 2020 |
| Lepard: Learning partial point cloud matching in rigid and deformable scenes Y Li, T Harada Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 153 | 2022 |
| Goal-oriented gaze estimation for zero-shot learning Y Liu, L Zhou, X Bai, Y Huang, L Gu, J Zhou, T Harada Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 148 | 2021 |
| You only need 90k parameters to adapt light: a light weight transformer for image enhancement and exposure correction Z Cui, K Li, L Gu, S Su, P Gao, Z Jiang, Y Qiao, T Harada arXiv preprint arXiv:2205.14871, 2022 | 136 | 2022 |
| Online growing neural gas for anomaly detection in changing surveillance scenes Q Sun, H Liu, T Harada Pattern Recognition 64, 187-201, 2017 | 134 | 2017 |
