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Minyoung Kim
Minyoung Kim
Samsung AI Center Cambridge UK, SeoulTech, Rutgers University, Carnegie Mellon University
Verified email at samsung.com - Homepage
Title
Cited by
Cited by
Year
Face tracking and recognition with visual constraints in real-world videos
M Kim, S Kumar, V Pavlovic, H Rowley
2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008
6202008
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference
SX Hu, D Li, J Stühmer, M Kim, TM Hospedales
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
1602022
Structured output ordinal regression for dynamic facial emotion intensity prediction
M Kim, V Pavlovic
European conference on computer vision, 649-662, 2010
662010
Gaussian Processes Multiple Instance Learning.
M Kim, F De la Torre
ICML, 535-542, 2010
642010
Fisher SAM: Information Geometry and Sharpness Aware Minimisation
M Kim, D Li, SX Hu, T Hospedales
International Conference on Machine Learning, 11148-11161, 2022
552022
Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach
M Kim, P Sahu, B Gholami, V Pavlovic
IEEE Conference on Computer Vision and Pattern Recognition, 2019
522019
Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement
M Kim, Y Wang, P Sahu, V Pavlovic
International Conference on Computer Vision (ICCV), 2979-2987, 2019
302019
Discriminative learning for dynamic state prediction
M Kim, V Pavlovic
IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (10), 1847 …, 2009
302009
Relevance Factor VAE: Learning and Identifying Disentangled Factors
M Kim, Y Wang, P Sahu, V Pavlovic
arXiv preprint arXiv:1902.01568, 2019
292019
Central subspace dimensionality reduction using covariance operators
M Kim, V Pavlovic
IEEE transactions on pattern analysis and machine intelligence 33 (4), 657-670, 2011
272011
Semi-supervised learning of hidden conditional random fields for time-series classification
M Kim
Neurocomputing 119, 339-349, 2013
262013
Dimensionality reduction using covariance operator inverse regression
M Kim, V Pavlovic
2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008
262008
Discriminative learning of mixture of bayesian network classifiers for sequence classification
M Kim, V Pavlovic
2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006
232006
Object tracking in video with visual constraints
M Kim, S Kumar, HA Rowley
US Patent 8,477,998, 2013
222013
Large margin cost-sensitive learning of conditional random fields
M Kim
Pattern Recognition 43 (10), 3683-3692, 2010
222010
Model-induced term-weighting schemes for text classification
HK Kim, M Kim
Applied Intelligence 45 (1), 30-43, 2016
212016
Correlation-based incremental visual tracking
M Kim
Pattern Recognition 45 (3), 1050-1060, 2012
212012
Object tracking in video with visual constraints
M Kim, S Kumar, HA Rowley
US Patent 8,085,982, 2011
202011
Hidden conditional ordinal random fields for sequence classification
M Kim, V Pavlovic
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010
202010
Mixtures of conditional random fields for improved structured output prediction
M Kim
IEEE transactions on neural networks and learning systems 28 (5), 1233-1240, 2017
182017
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