Follow
Mengyi Liu
Title
Cited by
Cited by
Year
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
4592014
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
3922014
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
3202013
Au-inspired deep networks for facial expression feature learning
M Liu, S Li, S Shan, X Chen
Neurocomputing 159, 126-136, 2015
2662015
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
2232014
A comprehensive survey on automatic facial action unit analysis
R Zhi, M Liu, D Zhang
The Visual Computer 36 (5), 1067-1093, 2020
1282020
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
802013
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
542016
Distortion-aware monocular depth estimation for omnidirectional images
HX Chen, K Li, Z Fu, M Liu, Z Chen, Y Guo
IEEE Signal Processing Letters 28, 334-338, 2021
342021
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
292012
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), 2015
212015
Pano-SfMLearner: Self-supervised Multi-task Learning of Depth and Semantics in Panoramic Videos
M Liu, S Wang, Y Guo, Y He, H Xue
IEEE Signal Processing Letters 28, 832-836, 2021
192021
深度学习: 多层神经网络的复兴与变革
山世光, 阚美娜, 刘昕, 刘梦怡, 邬书哲
科技导报 34 (14), 60-70, 2016
152016
Content-based video relevance prediction challenge: Data, protocol, and baseline (ACM Multimedia 2018 CBVRP Grand Challenge)
M Liu, X Xie, H Zhou
arXiv preprint arXiv:1806.00737, 2018
112018
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, 113-124, 2016
92016
Facial micro-expression recognition using enhanced temporal feature-wise model
R Zhi, M Liu, H Xu, M Wan
Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health …, 2019
72019
Deep Learning: The revival and transformation of multi layer neural networks
S SHAN, M KAN, X LIU, M LIU, S WU
Science & Technology Review 34 (14), 60-70, 2016
72016
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
72012
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
72011
Multi-stage information diffusion for joint depth and surface normal estimation
Z Fu, S Hong, M Liu, H Laga, M Bennamoun, F Boussaid, Y Guo
Pattern recognition 141, 109660, 2023
62023
The system can't perform the operation now. Try again later.
Articles 1–20