| Enhanced skeleton visualization for view invariant human action recognition M Liu, H Liu, C Chen Pattern Recognition (PR), 2017 | 890 | 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 | 371 | 2018 |
| Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation W Li, H Liu, R Ding, M Liu, P Wang, W Yang IEEE Transactions on Multimedia (TMM), 2022 | 248 | 2022 |
| Two-stream 3d convolutional neural network for skeleton-based action recognition H Liu, J Tu, M Liu arXiv preprint arXiv:1705.08106, 2017 | 195 | 2017 |
| A Survey on 3D Skeleton-Based Action Recognition Using Learning Method B Ren, M Liu, R Ding, H Liu Cyborg and Bionic Systems (CBS), 2024 | 194 | 2024 |
| Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-Supervised Action Recognition T Guo, H Liu, Z Chen, M Liu, T Wang, R Ding AAAI Conference on Artificial Intelligence (AAAI), 2022 | 165 | 2022 |
| PoseFormerV2: Exploring Frequency Domain for Efficient and Robust 3D Human Pose Estimation Q Zhao, C Zheng, M Liu, P Wang, C Chen IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 129 | 2023 |
| 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 | 85 | 2018 |
| CNN‐Based Reference Comparison Method for Classifying Bare PCB Defects P Wei, C Liu, M Liu, Y Gao, H Liu Journal of Engineering (JoE), 2018 | 84 | 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 | 84 | 2016 |
| Temporal Decoupling Graph Convolutional Network for Skeleton-Based Gesture Recognition J Liu, X Wang, C Wang, Y Gao, M Liu IEEE Transactions on Multimedia (TMM), 2024 | 82 | 2024 |
| Consistency-Based Active Learning for Object Detection W Yu, S Zhu, T Yang, C Chen, M Liu https://arxiv.org/abs/2103.10374v2, 2021 | 67 | 2021 |
| 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 | 65 | 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 | 64 | 2017 |
| Depth Context: A new descriptor for human activity recognition by using sole depth sequences M Liu, H Liu Neurocomputing, 2016 | 62 | 2016 |
| 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 (TIP), 2019 | 61 | 2019 |
| Skeleton-Based Human Action Recognition Using Spatial Temporal 3D Convolutional Neural Networks J Tu, M Liu, H Liu IEEE International conference on multimedia and expo (ICME), 2018 | 60 | 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 | 53 | 2018 |
| Robust 3D Action Recognition through Sampling Local Appearances and Global Distributions M Liu, H Liu, C Chen IEEE Transactions on Multimedia (TMM), 2018 | 48 | 2018 |
| Part Aware Contrastive Learning for Self-Supervised Action Recognition Y Hua, W Wu, C Zheng, A Lu, M Liu, C Chen, S Wu International Joint Conference on Artificial Intelligence (IJCAI), 2023 | 41 | 2023 |
Hong liuProfessor of Computer Science, Peking Universitypkusz.edu.cn의 이메일 확인됨