| Knowledge transfer via distillation of activation boundaries formed by hidden neurons B Heo, M Lee, S Yun, JY Choi Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3779-3787, 2019 | 552 | 2019 |
| Symmetric graph convolutional autoencoder for unsupervised graph representation learning J Park, M Lee, HJ Chang, K Lee, JY Choi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 277 | 2019 |
| Knowledge distillation with adversarial samples supporting decision boundary B Heo, M Lee, S Yun, JY Choi Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3771-3778, 2019 | 153 | 2019 |
| Procrustean Normal Distribution for Non-Rigid Structure from Motion M Lee, J Cho, S Oh IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (7), 1388-1400, 2017 | 109* | 2017 |
| Procrustean normal distribution for non-rigid structure from motion M Lee, J Cho, CH Choi, S Oh Proceedings of the IEEE Conference on computer vision and pattern …, 2013 | 109 | 2013 |
| Robust action recognition using local motion and group sparsity J Cho, M Lee, HJ Chang, S Oh Pattern Recognition 47 (5), 1813-1825, 2014 | 77 | 2014 |
| Elastic-net regularization of singular values for robust subspace learning E Kim, M Lee, S Oh Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 57 | 2015 |
| Efficient -Norm-Based Low-Rank Matrix Approximations for Large-Scale Problems Using Alternating Rectified Gradient Method E Kim, M Lee, CH Choi, N Kwak, S Oh IEEE transactions on neural networks and learning systems 26 (2), 237-251, 2015 | 49 | 2015 |
| Consensus of non-rigid reconstructions M Lee, J Cho, S Oh Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 46 | 2016 |
| A Procrustean Markov process for non-rigid structure recovery M Lee, CH Choi, S Oh Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 40 | 2014 |
| Membership representation for detecting block-diagonal structure in low-rank or sparse subspace clustering M Lee, J Lee, H Lee, N Kwak Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 31 | 2015 |
| Complex non-rigid 3d shape recovery using a procrustean normal distribution mixture model J Cho, M Lee, S Oh International Journal of Computer Vision 117 (3), 226-246, 2016 | 26 | 2016 |
| Procrustean Regression Networks: Learning 3D Structure of Non-Rigid Objects from 2D Annotations S Park, M Lee, N Kwak European Conference on Computer Vision, 1-18, 2020 | 21 | 2020 |
| Graph-matching-based correspondence search for nonrigid point cloud registration S Chang, C Ahn, M Lee, S Oh Computer Vision and Image Understanding 192, 102899, 2020 | 20 | 2020 |
| Real-time facial shape recovery from a single image under general, unknown lighting by rank relaxation M Lee, CH Choi Computer Vision and Image Understanding 120, 59-69, 2014 | 19 | 2014 |
| Building a Compact Convolutional Neural Network for Embedded Intelligent Sensor Systems Using Group Sparsity and Knowledge Distillation J Cho, M Lee Sensors 19 (19), 4307, 2019 | 17 | 2019 |
| Incremental -Mode SVD for Large-Scale Multilinear Generative Models M Lee, CH Choi IEEE Transactions on Image Processing 23 (10), 4255-4269, 2014 | 16 | 2014 |
| Unsupervised 3d reconstruction networks G Cha, M Lee, S Oh Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 15 | 2019 |
| Differentiable Forward and Backward Fixed-Point Iteration Layers Y Jeon, M Lee, JY Choi IEEE Access 9, 18383-18392, 2021 | 14 | 2021 |
| Generalized mean for feature extraction in one-class classification problems J Oh, N Kwak, M Lee, CH Choi Pattern Recognition 46 (12), 3328-3340, 2013 | 13 | 2013 |
Songhwai OhDepartment of Electrical and Computer Engineering, Seoul National University, KoreaVerified email at snu.ac.kr
