| 3d gan inversion with pose optimization J Ko, K Cho, D Choi, K Ryoo, S Kim Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 69 | 2023 |
| Conmatch: Semi-supervised learning with confidence-guided consistency regularization J Kim, Y Min, D Kim, G Lee, J Seo, K Ryoo, S Kim European Conference on Computer Vision, 674-690, 2022 | 53 | 2022 |
| Semi-supervised learning of semantic correspondence with pseudo-labels J Kim, K Ryoo, J Seo, G Lee, D Kim, H Cho, S Kim Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 20 | 2022 |
| SplitNet: learnable clean-noisy label splitting for learning with noisy labels D Kim, K Ryoo, H Cho, S Kim International Journal of Computer Vision 133 (2), 549-566, 2025 | 5 | 2025 |
| Towards flexible inductive bias via progressive reparameterization scheduling Y Lee, G Lee, K Ryoo, H Go, J Park, S Kim European Conference on Computer Vision, 706-720, 2022 | 4 | 2022 |
| Aggmatch: Aggregating pseudo labels for semi-supervised learning J Kim, K Ryoo, G Lee, S Cho, J Seo, D Kim, H Cho, S Kim arXiv preprint arXiv:2201.10444, 2022 | 3 | 2022 |
| Universal Noise Annotation: Unveiling the Impact of Noisy annotation on Object Detection K Ryoo, Y Jo, S Lee, M Kim, A Jo, SH Kim, S Kim, S Lee arXiv preprint arXiv:2312.13822, 2023 | 1 | 2023 |
| Correction: SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels D Kim, K Ryoo, H Cho, S Kim International Journal of Computer Vision, 1-1, 2025 | | 2025 |
| Unsupervised Open-Set Task Adaptation Using a Vision-Language Foundation Model Y Min, K Ryoo, B Kim, T Kim | | |
| UOTA: Unsupervised Open-Set Task Adaptation Using a Vision-Language Foundation Model Y Min, K Ryoo, B Kim, T Kim Workshop on Efficient Systems for Foundation Models@ ICML2023, 0 | | |
