I received a bachelor’s degree in Business Administration and Computer Science & Engineering from Korea University.
During my undergraduate studies, I worked at Korea University Computer Vision Laboratory as an undergraduate researcher, and conducted research on Semi-Supervised Learning, Semantic Correspondence, 3D Human Mesh Recovery, and Style Transfer.
I am currently exploring Representation Learning and Adaptation Algorithms with the ultimate goal of building data-efficient AI.
Controllable Style Transfer via Test-time Training of Implicit Neural Representation
Sunwoo Kim*, Youngjo Min*, Younghun Jung*, and Seungryong Kim
(* Equal Contribution)
International Journal of Computer Vision (IJCV, Under Review)
[Paper][Project]
ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization
Jiwon Kim*, Youngjo Min*, Daehwan Kim*, Gyuseong Lee, Junyoung Seo, Kwangrok Ryoo, and Seungryong Kim (* Equal Contribution)
2022 European Conference on Computer Vision (ECCV 2022)
[Paper][Project]
Meta-learned Initialization for 3D Human Recovery
Mira Kim, Youngjo Min, Jiwon Kim, and Seungryong Kim
2022 IEEE International Conference on Image Processing (ICIP 2022)
[Paper]
Joint Learning of Feature Extraction and Cost Aggregation for Semantic Correspondence
Jiwon Kim, Youngjo Min, Mira Kim, and Seungryong Kim
2022 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2022)
[Paper]
I am currently working on a paper about Domain Generalization & Adaptation, and I am planning to submit it to the 2023 International Conference on Machine Learning (ICML 2023)