| Proxy anchor loss for deep metric learning S Kim, D Kim, M Cho, S Kwak Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 414 | 2020 |
| Deep metric learning beyond binary supervision S Kim, M Seo, I Laptev, M Cho, S Kwak Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 120 | 2019 |
| Embedding transfer with label relaxation for improved metric learning S Kim, D Kim, M Cho, S Kwak Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 39 | 2021 |
| Cross-domain ensemble distillation for domain generalization K Lee, S Kim, S Kwak European Conference on Computer Vision, 1-20, 2022 | 29 | 2022 |
| Promptstyler: Prompt-driven style generation for source-free domain generalization J Cho, G Nam, S Kim, H Yang, S Kwak Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 26 | 2023 |
| Combating label distribution shift for active domain adaptation S Hwang, S Lee, S Kim, J Ok, S Kwak European Conference on Computer Vision, 549-566, 2022 | 15 | 2022 |
| Self-taught metric learning without labels S Kim, D Kim, M Cho, S Kwak Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 15 | 2022 |
| Hier: Metric learning beyond class labels via hierarchical regularization S Kim, B Jeong, S Kwak Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
| Learning to generate novel classes for deep metric learning K Lee, S Kim, S Hong, S Kwak arXiv preprint arXiv:2201.01008, 2022 | 1 | 2022 |
| Universal Metric Learning with Parameter-Efficient Transfer Learning S Kim, D Kim, S Kwak arXiv preprint arXiv:2309.08944, 2023 | | 2023 |
| Embedding Transfer via Smooth Contrastive Loss S Kim, D Kim, M Cho, S Kwak | | |
Suha KwakPOSTECH在 postech.ac.kr 的电子邮件经过验证
