Sanghyun Jo - Google Scholar

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Citations	167	167
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202020212022202320241 5 35 59 60

Co-authors

In-Jae YuSamsung ElectronicsVerified email at samsung.com
Kyungsu KimSeoul National UniversityVerified email at snu.ac.kr
Eunho YangKAISTVerified email at kaist.ac.kr
Soohyun RyuKAIST AI PhD candidateVerified email at mli.kaist.ac.kr
Fei PanResearch Fellow at CSE, University of MichiganVerified email at umich.edu

Sanghyun Jo

Sanghyun Jo

OGQ

Verified email at ogqcorp.com - Homepage

Weakly-supervised Segmentation Data-efficient Learning Generative AI


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Puzzle-cam: Improved localization via matching partial and full features S Jo, IJ Yu 2021 IEEE international conference on image processing (ICIP), 639-643, 2021	122	2021
MARS: Model-agnostic Biased Object Removal without Additional Supervision for Weakly-Supervised Semantic Segmentation S Jo, IJ Yu, K Kim ICCV 2023, 2023	18	2023
RecurSeed and EdgePredictMix: Pseudo-Label Refinement Learning for Weakly Supervised Semantic Segmentation across Single- and Multi-Stage Frameworks S Jo, IJ Yu, K Kim arXiv preprint arXiv:2204.06754, 2022	16*	2022
RecurSeed and CertainMix for Weakly Supervised Semantic Segmentation S Jo, IJ Yu, K Kim arXiv preprint arXiv:2204.06754 1, 2022	10	2022
TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias S Jo, S Ryu, S Kim, E Yang, K Kim ECCV 2024, 2024	1	2024
DHR: Dual Features-Driven Hierarchical Rebalancing in Inter-and Intra-Class Regions for Weakly-Supervised Semantic Segmentation S Jo, F Pan, IJ Yu, K Kim ECCV 2024, 2024		2024
Supplementary Material MARS: Model-agnostic Biased Object Removal without Additional Supervision for Weakly-Supervised Semantic Segmentation S Jo, IJ Yu, K Kim

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