| Enhanced skeleton visualization for view invariant human action recognition M Liu, H Liu, C Chen Pattern Recognition (PR), 2017 | 322 | 2017 |
| Recognizing Human Actions as the Evolution of Pose Estimation Maps M Liu, J Yuan IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2018 | 113 | 2018 |
| 3D Action Recognition Using Multi-temporal Depth Motion Maps and Fisher Vector C Chen, M Liu, B Zhang, J Han, J Jiang, H Liu International Joint Conference on Artificial Intelligence (IJCAI), 2016 | 63 | 2016 |
| Two-Stream 3D Convolutional Neural Network for Skeleton-Based Action Recognition H Liu, J Tu, M Liu arXiv preprint arXiv:1705.08106, 2017 | 55 | 2017 |
| Depth Context: A new descriptor for human activity recognition by using sole depth sequences M Liu, H Liu Neurocomputing, 2016 | 44 | 2016 |
| Multi-Temporal Depth Motion Maps-Based Local Binary Patterns for 3-D Human Action Recognition C Chen, M Liu, H Liu, B Zhang, J Han, N Kehtarnavaz IEEE Access, 2017 | 38 | 2017 |
| Action recognition from depth sequences using weighted fusion of 2D and 3D auto-correlation of gradients features C Chen, B Zhang, Z Hou, J Jiang, M Liu, Y Yang Multimedia Tools and Applications (MTA), 2017 | 36 | 2017 |
| Deformable Pose Traversal Convolution for 3D Action and Gesture Recognition J Weng, M Liu, X Jiang, J Yuan European Conference on Computer Vision (ECCV), 2018 | 29 | 2018 |
| Robust 3D Action Recognition through Sampling Local Appearances and Global Distributions M Liu, H Liu, C Chen IEEE Transactions on Multimedia (T-MM), 2017 | 24 | 2017 |
| Learning Directional Co-occurrence for Human Action Classification H Liu, M Liu, Q Sun IEEE International Conference on Acoustics, Speech and Signal Processing …, 2014 | 22 | 2014 |
| 3D Action Recognition Using Multi-scale Energy-based Global Ternary Image M Liu, H Liu, C Chen IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 2017 | 21 | 2017 |
| Human action recognition using adaptive hierarchical depth motion maps and gabor filter H Liu, Q He, M Liu IEEE International Conference on Acoustics, Speech and Signal Processing …, 2017 | 18 | 2017 |
| CNN-based reference comparison method for classifying bare PCB defects P Wei, C Liu, M Liu, Y Gao, H Liu The Journal of Engineering 2018 (16), 1528-1533, 2018 | 16 | 2018 |
| Salient pairwise spatio-temporal interest points for real-time activity recognition M Liu, H Liu, Q Sun, T Zhang, R Ding CAAI Transactions on Intelligence Technology (CAAI-TIT), 2016 | 16 | 2016 |
| A survey on 3d skeleton-based action recognition using learning method B Ren, M Liu, R Ding, H Liu arXiv preprint arXiv:2002.05907, 2020 | 14 | 2020 |
| Spatial-temporal data augmentation based on LSTM autoencoder network for skeleton-based human action recognition J Tu, H Liu, F Meng, M Liu, R Ding IEEE International Conference on Image Processing (ICIP), 2018 | 14 | 2018 |
| 3D action recognition using data visualization and convolutional neural networks M Liu, C Chen, H Liu IEEE International Conference on Multimedia and Expo (ICME), 2017 | 13 | 2017 |
| Action classification by exploring directional co-occurrence of weighted STIPs M Liu, H Liu, Q Sun IEEE International Conference on Image Processing (ICIP), 2014 | 13 | 2014 |
| SDM-BSM: A fusing depth scheme for human action recognition H Liu, L Tian, M Liu IEEE International Conference on Image Processing (ICIP), 2015 | 12 | 2015 |
| Sample Fusion Network: An End-to-End Data Augmentation Network for Skeleton-based Human Action Recognition F Meng, H Liu, Y Liang, J Tu, M Liu IEEE Transactions on Image Processing (T-IP), 2019 | 10 | 2019 |
Hong liuProfessor of Computer Science, Peking UniversityVerified email at pkusz.edu.cn
