| Enhanced skeleton visualization for view invariant human action recognition M Liu, H Liu, C Chen Pattern Recognition (PR), 2017 | 254 | 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 | 73 | 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 | 58 | 2016 |
| Depth Context: A new descriptor for human activity recognition by using sole depth sequences M Liu, H Liu Neurocomputing, 2016 | 40 | 2016 |
| 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 | 34 | 2017 |
| 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 | 33 | 2017 |
| Two-Stream 3D Convolutional Neural Network for Skeleton-Based Action Recognition H Liu, J Tu, M Liu arXiv preprint arXiv:1705.08106, 2017 | 30 | 2017 |
| Robust 3D Action Recognition through Sampling Local Appearances and Global Distributions M Liu, H Liu, C Chen IEEE Transactions on Multimedia (T-MM), 2017 | 22 | 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 | 21 | 2014 |
| 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 | 20 | 2018 |
| 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 | 18 | 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 | 16 | 2017 |
| 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 | 15 | 2016 |
| 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 |
| Action classification by exploring directional co-occurrence of weighted STIPs M Liu, H Liu, Q Sun IEEE International Conference on Image Processing (ICIP), 2014 | 12 | 2014 |
| 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 | 11 | 2018 |
| 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 | 10 | 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 | 10 | 2017 |
| Energy-based global ternary image for action recognition using sole depth sequences M Liu, H Liu, C Chen, M Najafian International Conference on 3D Vision (3DV), 2016 | 10 | 2016 |
| Fusing shape and motion matrices for view invariant action recognition using 3D skeletons M Liu, Q He, H Liu IEEE International Conference on Image Processing (ICIP), 2017 | 9 | 2017 |
Hong liuProfessor of Computer Science, Peking UniversityVerified email at pkusz.edu.cn
