| 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 | 2366 | 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 | 787 | 2019 |
| Semi-supervised domain adaptation via minimax entropy K Saito, D Kim, S Sclaroff, T Darrell, K Saenko Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 777 | 2019 |
| Asymmetric Tri-training for Unsupervised Domain Adaptation K Saito, Y Ushiku, T Harada ICML 2017, 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 |
| Universal domain adaptation through self supervision K Saito, D Kim, S Sclaroff, K Saenko Advances in neural information processing systems 33, 16282-16292, 2020 | 374 | 2020 |
| Adversarial dropout regularization K Saito, Y Ushiku, T Harada, K Saenko arXiv preprint arXiv:1711.01575, 2017 | 340 | 2017 |
| Ovanet: One-vs-all network for universal domain adaptation K Saito, K Saenko Proceedings of the ieee/cvf international conference on computer vision …, 2021 | 170 | 2021 |
| Coco-funit: Few-shot unsupervised image translation with a content conditioned style encoder K Saito, K Saenko, MY Liu Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 106 | 2020 |
| Syn2real: A new benchmark forsynthetic-to-real visual domain adaptation X Peng, B Usman, K Saito, N Kaushik, J Hoffman, K Saenko arXiv preprint arXiv:1806.09755, 2018 | 99 | 2018 |
| Pic2word: Mapping pictures to words for zero-shot composed image retrieval K Saito, K Sohn, X Zhang, CL Li, CY Lee, K Saenko, T Pfister Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 83 | 2023 |
| Openmatch: Open-set semi-supervised learning with open-set consistency regularization K Saito, D Kim, K Saenko Advances in Neural Information Processing Systems 34, 25956-25967, 2021 | 81 | 2021 |
| Dualnet: Domain-invariant network for visual question answering K Saito, A Shin, Y Ushiku, T Harada 2017 IEEE International Conference on Multimedia and Expo (ICME), 829-834, 2017 | 79 | 2017 |
| Spatio-temporal person retrieval via natural language queries M Yamaguchi, K Saito, Y Ushiku, T Harada Proceedings of the IEEE international conference on computer vision, 1453-1462, 2017 | 69 | 2017 |
| Openmatch: Open-set consistency regularization for semi-supervised learning with outliers K Saito, D Kim, K Saenko arXiv preprint arXiv:2105.14148, 2021 | 68 | 2021 |
| Tune it the right way: Unsupervised validation of domain adaptation via soft neighborhood density K Saito, D Kim, P Teterwak, S Sclaroff, T Darrell, K Saenko Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 60 | 2021 |
| Learning to detect every thing in an open world K Saito, P Hu, T Darrell, K Saenko European Conference on Computer Vision, 268-284, 2022 | 55 | 2022 |
| Cds: Cross-domain self-supervised pre-training D Kim, K Saito, TH Oh, BA Plummer, S Sclaroff, K Saenko Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 52 | 2021 |
| Cross-domain self-supervised learning for domain adaptation with few source labels D Kim, K Saito, TH Oh, BA Plummer, S Sclaroff, K Saenko arXiv preprint arXiv:2003.08264, 2020 | 49 | 2020 |
| Mule: Multimodal universal language embedding D Kim, K Saito, K Saenko, S Sclaroff, B Plummer Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 11254 …, 2020 | 36 | 2020 |
Kate SaenkoBoston UniversityVahvistettu sähköpostiosoite verkkotunnuksessa bu.edu
