Follow
Seunghoon Hong
Seunghoon Hong
Assistant Professor, KAIST
Verified email at kaist.ac.kr - Homepage
Title
Cited by
Cited by
Year
Learning deconvolution network for semantic segmentation
H Noh, S Hong, B Han
Proceedings of the IEEE international conference on computer vision, 1520-1528, 2015
54272015
Online tracking by learning discriminative saliency map with convolutional neural network
S Hong, T You, S Kwak, B Han
International conference on machine learning, 597-606, 2015
10502015
Decomposing motion and content for natural video sequence prediction
R Villegas, J Yang, S Hong, X Lin, H Lee
arXiv preprint arXiv:1706.08033, 2017
6542017
Inferring semantic layout for hierarchical text-to-image synthesis
S Hong, D Yang, J Choi, H Lee
Proceedings of the IEEE conference on computer vision and pattern …, 2018
5532018
Decoupled deep neural network for semi-supervised semantic segmentation
S Hong, H Noh, B Han
Advances in neural information processing systems 28, 2015
4072015
Diversity-sensitive conditional generative adversarial networks
D Yang, S Hong, Y Jang, T Zhao, H Lee
arXiv preprint arXiv:1901.09024, 2019
2192019
Learning transferrable knowledge for semantic segmentation with deep convolutional neural network
S Hong, J Oh, H Lee, B Han
Proceedings of the IEEE conference on computer vision and pattern …, 2016
2142016
Weakly supervised semantic segmentation using web-crawled videos
S Hong, D Yeo, S Kwak, H Lee, B Han
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
1842017
Weakly supervised semantic segmentation using superpixel pooling network
S Kwak, S Hong, B Han
Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017
1502017
Part-based pseudo label refinement for unsupervised person re-identification
Y Cho, WJ Kim, S Hong, SE Yoon
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
1292022
The visual object tracking VOT2016 challenge results
G Roffo, S Melzi
Computer Vision--ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016
1152016
Pure transformers are powerful graph learners
J Kim, D Nguyen, S Min, S Cho, M Lee, H Lee, S Hong
Advances in Neural Information Processing Systems 35, 14582-14595, 2022
1062022
Learning hierarchical semantic image manipulation through structured representations
S Hong, X Yan, TS Huang, H Lee
Advances in Neural Information Processing Systems 31, 2018
862018
Improving unsupervised image clustering with robust learning
S Park, S Han, S Kim, D Kim, S Park, S Hong, M Cha
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
852021
Adversarial defense via learning to generate diverse attacks
Y Jang, T Zhao, S Hong, H Lee
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
832019
High-fidelity synthesis with disentangled representation
W Lee, D Kim, S Hong, H Lee
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
712020
Setvae: Learning hierarchical composition for generative modeling of set-structured data
J Kim, J Yoo, J Lee, S Hong
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
552021
Online graph-based tracking
H Nam, S Hong, B Han
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
512014
Weakly supervised learning with deep convolutional neural networks for semantic segmentation: Understanding semantic layout of images with minimum human supervision
S Hong, S Kwak, B Han
IEEE Signal Processing Magazine 34 (6), 39-49, 2017
482017
Object recognition apparatus and method
B Han, H Seunghoon, NOH Hyeonwoo
US Patent 9,940,539, 2018
462018
The system can't perform the operation now. Try again later.
Articles 1–20