Kihyuk Sohn
Kihyuk Sohn
Research Scientist, Google
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Learning structured output representation using deep conditional generative models
K Sohn, H Lee, X Yan
Advances in neural information processing systems 28, 3483-3491, 2015
15022015
Improved deep metric learning with multi-class n-pair loss objective
K Sohn
Advances in neural information processing systems, 1857-1865, 2016
9202016
Attribute2image: Conditional image generation from visual attributes
X Yan, J Yang, K Sohn, H Lee
European Conference on Computer Vision, 776-791, 2016
6742016
Learning to adapt structured output space for semantic segmentation
YH Tsai, WC Hung, S Schulter, K Sohn, MH Yang, M Chandraker
Proceedings of the IEEE conference on computer vision and pattern …, 2018
6562018
Fixmatch: Simplifying semi-supervised learning with consistency and confidence
K Sohn, D Berthelot, CL Li, Z Zhang, N Carlini, ED Cubuk, A Kurakin, ...
arXiv preprint arXiv:2001.07685, 2020
4582020
Understanding and improving convolutional neural networks via concatenated rectified linear units
W Shang, K Sohn, D Almeida, H Lee
international conference on machine learning, 2217-2225, 2016
3962016
Towards large-pose face frontalization in the wild
X Yin, X Yu, K Sohn, X Liu, M Chandraker
Proceedings of the IEEE international conference on computer vision, 3990-3999, 2017
2582017
Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring
D Berthelot, N Carlini, ED Cubuk, A Kurakin, K Sohn, H Zhang, C Raffel
arXiv preprint arXiv:1911.09785, 2019
2522019
Learning to disentangle factors of variation with manifold interaction
S Reed, K Sohn, Y Zhang, H Lee
International conference on machine learning, 1431-1439, 2014
2372014
Improving object detection with deep convolutional networks via bayesian optimization and structured prediction
Y Zhang, K Sohn, R Villegas, G Pan, H Lee
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
2102015
Augmenting CRFs with Boltzmann machine shape priors for image labeling
A Kae, K Sohn, H Lee, E Learned-Miller
Proceedings of the IEEE conference on computer vision and pattern …, 2013
2032013
Online incremental feature learning with denoising autoencoders
G Zhou, K Sohn, H Lee
Artificial intelligence and statistics, 1453-1461, 2012
1842012
Learning invariant representations with local transformations
K Sohn, H Lee
international conference on machine learning, 2012
1792012
Improved multimodal deep learning with variation of information
K Sohn, W Shang, H Lee
Advances in neural information processing systems 27, 2141-2149, 2014
1732014
Efficient learning of sparse, distributed, convolutional feature representations for object recognition
K Sohn, DY Jung, H Lee, AO Hero
2011 International Conference on Computer Vision, 2643-2650, 2011
1562011
Feature transfer learning for face recognition with under-represented data
X Yin, X Yu, K Sohn, X Liu, M Chandraker
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
149*2019
Domain adaptation for structured output via discriminative patch representations
YH Tsai, K Sohn, S Schulter, M Chandraker
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
1342019
Reconstruction-based disentanglement for pose-invariant face recognition
X Peng, X Yu, K Sohn, DN Metaxas, M Chandraker
Proceedings of the IEEE international conference on computer vision, 1623-1632, 2017
1322017
Learning and selecting features jointly with point-wise gated {B} oltzmann machines
K Sohn, G Zhou, C Lee, H Lee
Proceedings of The 30th International Conference on Machine Learning, 217-225, 2013
1092013
Unsupervised domain adaptation for face recognition in unlabeled videos
K Sohn, S Liu, G Zhong, X Yu, MH Yang, M Chandraker
Proceedings of the IEEE International Conference on Computer Vision, 3210-3218, 2017
982017
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