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Seungho Lee
Seungho Lee
Yonsei University
Dirección de correo verificada de yonsei.ac.kr
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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
2102021
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
2012020
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
232022
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
52023
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
32022
Weakly Supervised Semantic Segmentation for Driving Scenes
D Kim, S Lee, J Choe, H Shim
Proceedings of the AAAI Conference on Artificial Intelligence 38 (3), 2741-2749, 2024
2024
Weakly supervised semantic segmentation device and method based on pseudo-masks
H Shim, S Lee, M Lee
US Patent 11,798,171, 2023
2023
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
2020
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