Sung-Hoon Yoon
Orcid: 0000-0001-5851-2031Affiliations:
- Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea
- Harvard University, Harvard AI and Robotics Lab, Boston, MA, USA
- Korea Advanced Institute of Science and Technology (KAIST), Department of Mechanical Engineering, Visual Intelligence Lab, Daejeon, South Korea (PhD 2024)
According to our database1,
Sung-Hoon Yoon authored at least 14 papers
between 2021 and 2026.
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Bibliography
2026
CoRR, February, 2026
2025
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025
2024
Proceedings of the Computer Vision - ECCV 2024, 2024
Phase Concentration and Shortcut Suppression for Weakly Supervised Semantic Segmentation.
Proceedings of the Computer Vision - ECCV 2024, 2024
Proceedings of the Computer Vision - ECCV 2024, 2024
Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event Cameras.
Proceedings of the Computer Vision - ECCV 2024, 2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-Specific Token Memory.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
Weakly Supervised Semantic Segmentation via Adversarial Learning of Classifier and Reconstructor.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Adversarial Erasing Framework via Triplet with Gated Pyramid Pooling Layer for Weakly Supervised Semantic Segmentation.
Proceedings of the Computer Vision - ECCV 2022, 2022
2021
CoRR, 2021
Unlocking the Potential of Ordinary Classifier: Class-specific Adversarial Erasing Framework for Weakly Supervised Semantic Segmentation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
EvDistill: Asynchronous Events To End-Task Learning via Bidirectional Reconstruction-Guided Cross-Modal Knowledge Distillation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021