| Evaluating weakly supervised object localization methods right J Choe, SJ Oh, S Lee, S Chun, Z Akata, H Shim Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 184 | 2020 |
| Railroad is not a train: Saliency as pseudo-pixel supervision for weakly supervised semantic segmentation S Lee, M Lee, J Lee, H Shim Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 159 | 2021 |
| Attention-based dropout layer for weakly supervised single object localization and semantic segmentation J Choe, S Lee, H Shim IEEE transactions on pattern analysis and machine intelligence 43 (12), 4256 …, 2020 | 83 | 2020 |
| Evaluation for weakly supervised object localization: Protocol, metrics, and datasets J Choe, SJ Oh, S Chun, S Lee, Z Akata, H Shim IEEE transactions on pattern analysis and machine intelligence 45 (2), 1732-1748, 2022 | 19 | 2022 |
| Saliency as Pseudo-Pixel Supervision for Weakly and Semi-Supervised Semantic Segmentation M Lee, S Lee, J Lee, H Shim IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 1 | 2023 |
| Learning from Better Supervision: Self-distillation for Learning with Noisy Labels K Baek, S Lee, H Shim 2022 26th International Conference on Pattern Recognition (ICPR), 1829-1835, 2022 | 1 | 2022 |
| Weakly supervised semantic segmentation device and method based on pseudo-masks S Hyunjung, S Lee, LEE Minhyun US Patent 11,798,171, 2023 | | 2023 |
Hyunjung ShimAssociate Professor, KAISTVerified email at kaist.ac.kr
