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Su Been Lee
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2020 – today
- 2024
- [c5]Suho Park, Su Been Lee, Sangeek Hyun, Hyun Seok Seong, Jae-Pil Heo:
Task-Disruptive Background Suppression for Few-Shot Segmentation. AAAI 2024: 4442-4449 - 2023
- [c4]Hyun Seok Seong, WonJun Moon, Su Been Lee, Jae-Pil Heo:
Leveraging Hidden Positives for Unsupervised Semantic Segmentation. CVPR 2023: 19540-19549 - [i5]Hyun Seok Seong, WonJun Moon, Su Been Lee, Jae-Pil Heo:
Leveraging Hidden Positives for Unsupervised Semantic Segmentation. CoRR abs/2303.15014 (2023) - [i4]Su Been Lee, WonJun Moon, Hyun Seok Seong, Jae-Pil Heo:
Task-Oriented Channel Attention for Fine-Grained Few-Shot Classification. CoRR abs/2308.00093 (2023) - [i3]WonJun Moon, Sangeek Hyun, Su Been Lee, Jae-Pil Heo:
Correlation-guided Query-Dependency Calibration in Video Representation Learning for Temporal Grounding. CoRR abs/2311.08835 (2023) - [i2]Suho Park, Su Been Lee, Sangeek Hyun, Hyun Seok Seong, Jae-Pil Heo:
Task-Disruptive Background Suppression for Few-Shot Segmentation. CoRR abs/2312.15894 (2023) - 2022
- [c3]John Laurentiev, Mufaddal Mahesri, Lily Bessette, Cassandra York, Heidi Zakoul, Su Been Lee, Dae Hyun Kim, Li Zhou, Joshua Lin:
Evaluation of a Machine Learning Approach to Identify ADL Impairment in Clinical Notes of People with Dementia. AMIA 2022 - [c2]Su Been Lee, WonJun Moon, Jae-Pil Heo:
Task Discrepancy Maximization for Fine-grained Few-Shot Classification. CVPR 2022: 5321-5330 - [i1]Su Been Lee, WonJun Moon, Jae-Pil Heo:
Task Discrepancy Maximization for Fine-grained Few-Shot Classification. CoRR abs/2207.01376 (2022) - 2021
- [c1]Su Been Lee, Jun Ho Park, Ji Young Kim, Seung Yeol Lee, Jae-Pil Heo:
Regularization with Multiple Feature Combination for Few-Shot Learning. BigComp 2021: 334-337
Coauthor Index
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