| Learning Expressionlets on Spatio-Temporal Manifold for Dynamic Facial Expression Recognition M Liu, S Shan, R Wang, X Chen Computer Vision and Pattern Recognition. CVPR 2014. IEEE, 1749-1756, 2014 | 272 | 2014 |
| Deeply Learning Deformable Facial Action Parts Model for Dynamic Expression Analysis M Liu, S Li, S Shan, R Wang, X Chen Asian Conference on Computer Vision. ACCV 2014. Springer, 143-157, 2014 | 226 | 2014 |
| AU-aware Deep Networks for Facial Expression Recognition M Liu, S Li, S Shan, X Chen Automatic Face and Gesture Recognition. FG 2013. IEEE, 1-6, 2013 | 199 | 2013 |
| Combining Multiple Kernel Methods on Riemannian Manifold for Emotion Recognition in the Wild M Liu, R Wang, S Li, S Shan, Z Huang, X Chen International Conference on Multimodal Interaction. ICMI 2014. ACM, 494-501, 2014 | 154 | 2014 |
| Au-inspired deep networks for facial expression feature learning M Liu, S Li, S Shan, X Chen Neurocomputing 159, 126-136, 2015 | 132 | 2015 |
| Partial least squares regression on grassmannian manifold for emotion recognition M Liu, R Wang, Z Huang, S Shan, X Chen International Conference on Multimodal Interaction. ICMI 2013. ACM, 525-530, 2013 | 60 | 2013 |
| Learning expressionlets via universal manifold model for dynamic facial expression recognition M Liu, S Shan, R Wang, X Chen IEEE Transactions on Image Processing 25 (12), 5920-5932, 2016 | 28 | 2016 |
| Enhancing expression recognition in the wild with unlabeled reference data M Liu, S Li, S Shan, X Chen Asian Conference on Computer Vision. ACCV 2012. Springer, 577-588, 2012 | 26 | 2012 |
| Exploiting Feature Hierarchies With Convolutional Neural Networks for Cultural Event Recognition M Liu, X Liu, Y Li, X Chen, A Hauptmann, S Shan IEEE International Conference on Computer Vision (ICCV) Workshops, 32-37, 2015 | 12 | 2015 |
| Content-based video relevance prediction challenge: Data, protocol, and baseline M Liu, X Xie, H Zhou arXiv preprint arXiv:1806.00737, 2018 | 8 | 2018 |
| Video modeling and learning on Riemannian manifold for emotion recognition in the wild M Liu, R Wang, S Li, Z Huang, S Shan, X Chen Journal on Multimodal User Interfaces 10 (2), 113-124, 2016 | 6 | 2016 |
| Heterogeneous face biometrics based on Guassian weights and invariant features synthesis M Liu, W Xie, X Chen, Y Ma, Y Guo, J Meng, Z Yuan, Q Qin Computing, Control and Industrial Engineering. CCIE 2011. IEEE 2, 374-377, 2011 | 6 | 2011 |
| A comprehensive survey on automatic facial action unit analysis R Zhi, M Liu, D Zhang The Visual Computer, 1-27, 2019 | 5 | 2019 |
| Learning mid-level words on Riemannian manifold for action recognition M Liu, R Wang, S Shan, X Chen arXiv preprint arXiv:1511.04808, 2015 | 5 | 2015 |
| Heterogeneous Face Recognition and Synthesis Using Canonical Correlation Analysis (CCA) M Liu, Z Yuan, Y Ma, X Chen, Q Yin Journal of Convergence Information Technology 7 (8), 398-407, 2012 | 5 | 2012 |
| An analysis-by-synthesis method based on sparse representation for heterogeneous face biometrics Y Ma, W Xie, X Chen, M Liu, Y Guo, J Meng, Z Yuan, Q Qin 2011 International Conference on Multimedia Technology, 148-151, 2011 | 5 | 2011 |
| The GA solution of dynamic Spectrum allocation in cognitive radio based on collaboration and fairness M Liu, H Zhang, R Fan, Z Duan 2011 Third Pacific-Asia Conference on Circuits, Communications and System …, 2011 | 5 | 2011 |
| Skipping word: A character-sequential representation based framework for question answering L Meng, Y Li, M Liu, P Shu Proceedings of the 25th ACM International on Conference on Information and …, 2016 | 3 | 2016 |
| Learning prototypes and similes on Grassmann manifold for spontaneous expression recognition M Liu, R Wang, S Shan, X Chen Computer Vision and Image Understanding 147, 95-101, 2016 | 3 | 2016 |
| Deep learning: The revival and transformation of multi layer neural networks SG SHAN, MN KAN, X LIU, M LIU, S WU Science & Technology Review 34 (14), 60-70, 2016 | 3 | 2016 |
Shiguang ShanProfessor of Institute of Computing Technology, Chinese Academy of SciencesVerified email at ict.ac.cn
