| 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 | 89* | 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 | 89 | 2013 |
| 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, 3779-3787, 2019 | 62 | 2019 |
| Robust action recognition using local motion and group sparsity J Cho, M Lee, HJ Chang, S Oh Pattern Recognition 47 (5), 1813-1825, 2014 | 59 | 2014 |
| 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 | 43 | 2015 |
| 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, 3771-3778, 2019 | 37 | 2019 |
| 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 | 37 | 2015 |
| Consensus of non-rigid reconstructions M Lee, J Cho, S Oh Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 36 | 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 | 33 | 2014 |
| 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 |
| 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 | 21 | 2015 |
| Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning J Park, M Lee, HJ Chang, K Lee, JY Choi Proceedings of the IEEE International Conference on Computer Vision, 6519-6528, 2019 | 17 | 2019 |
| 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 | 15 | 2014 |
| 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 | 12 | 2013 |
| Period-controlled MAC for high performance in wireless networks M Lee, Y Kim, CH Choi IEEE/ACM Transactions on Networking 19 (4), 1237-1250, 2011 | 12 | 2011 |
| Incremental -Mode SVD for Large-Scale Multilinear Generative Models M Lee, CH Choi IEEE Transactions on Image Processing 23 (10), 4255-4269, 2014 | 11 | 2014 |
| Fast facial shape recovery from a single image with general, unknown lighting by using tensor representation M Lee, CH Choi Pattern Recognition 44 (7), 1487-1496, 2011 | 11 | 2011 |
| Robust Elastic-Net Subspace Representation E Kim, M Lee, S Oh IEEE Transactions on Image Processing 25 (9), 4245-4259, 2016 | 10 | 2016 |
| Robust albedo estimation from a facial image with cast shadow under general unknown lighting S Suh, M Lee, CH Choi IEEE transactions on image processing 22 (1), 391-401, 2013 | 10 | 2013 |
| EM-GPA: Generalized Procrustes analysis with hidden variables for 3D shape modeling J Cho, M Lee, CH Choi, S Oh Computer Vision and Image Understanding 117 (11), 1549-1559, 2013 | 8 | 2013 |
Songhwai OhDepartment of Electrical and Computer Engineering, Seoul National University, KoreaVerified email at snu.ac.kr
