| Graph convolutional label noise cleaner: Train a plug-and-play action classifier for anomaly detection JX Zhong, N Li, W Kong, S Liu, TH Li, G Li Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 535 | 2019 |
| Video anomaly detection based on a hierarchical activity discovery within spatio-temporal contexts D Xu, R Song, X Wu, N Li, W Feng, H Qian Neurocomputing 143, 144-152, 2014 | 126 | 2014 |
| Step-by-step erasion, one-by-one collection: a weakly supervised temporal action detector JX Zhong, N Li, W Kong, T Zhang, TH Li, G Li Proceedings of the 26th ACM international conference on Multimedia, 35-44, 2018 | 98 | 2018 |
| Spatio-temporal context analysis within video volumes for anomalous-event detection and localization N Li, X Wu, D Xu, H Guo, W Feng Neurocomputing 155, 309-319, 2015 | 91 | 2015 |
| Attpool: Towards hierarchical feature representation in graph convolutional networks via attention mechanism J Huang, Z Li, N Li, S Liu, G Li Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 85 | 2019 |
| Image Cationing with Visual-Semantic LSTM. N Li, Z Chen IJCAI, 793-799, 2018 | 49 | 2018 |
| Hierarchical activity discovery within spatio-temporal context for video anomaly detection D Xu, X Wu, D Song, N Li, YL Chen 2013 IEEE International Conference on Image Processing, 3597-3601, 2013 | 43 | 2013 |
| Anomaly detection in video surveillance via gaussian process N Li, X Wu, H Guo, D Xu, Y Ou, YL Chen International Journal of Pattern Recognition and Artificial Intelligence 29 …, 2015 | 42 | 2015 |
| Sap: Self-adaptive proposal model for temporal action detection based on reinforcement learning J Huang, N Li, T Zhang, G Li, T Huang, W Gao Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 34 | 2018 |
| Spatial–temporal context-aware online action detection and prediction J Huang, N Li, T Li, S Liu, G Li IEEE Transactions on Circuits and Systems for Video Technology 30 (8), 2650-2662, 2019 | 24 | 2019 |
| Weakly-supervised anomaly detection in video surveillance via graph convolutional label noise cleaning N Li, JX Zhong, X Shu, H Guo Neurocomputing 481, 154-167, 2022 | 23 | 2022 |
| Meta learning for image captioning N Li, Z Chen, S Liu Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 8626-8633, 2019 | 23 | 2019 |
| Quaternion discrete cosine transformation signature analysis in crowd scenes for abnormal event detection H Guo, X Wu, S Cai, N Li, J Cheng, YL Chen Neurocomputing 204, 106-115, 2016 | 18 | 2016 |
| Toward visual distortion in black-box attacks N Li, Z Chen IEEE Transactions on Image Processing 30, 6156-6167, 2021 | 15 | 2021 |
| Searching action proposals via spatial actionness estimation and temporal path inference and tracking N Li, D Xu, Z Ying, Z Li, G Li Computer Vision–ACCV 2016: 13th Asian Conference on Computer Vision, Taipei …, 2017 | 14 | 2017 |
| Calibration of non-overlapping cameras based on a mobile robot H Huang, N Li, H Guo, YL Chen, X Wu 2015 5th International Conference on Information Science and Technology …, 2015 | 14 | 2015 |
| Multi-scale analysis of contextual information within spatio-temporal video volumes for anomaly detection N Li, H Guo, D Xu, X Wu 2014 IEEE International Conference on Image Processing (ICIP), 2363-2367, 2014 | 14 | 2014 |
| Anomaly detection and localization in crowded scenes using short-term trajectories H Guo, X Wu, N Li, R Fu, G Liang, W Feng 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO), 245-249, 2013 | 13 | 2013 |
| A survey on capsule networks: Evolution, application, and future development J Li, Q Zhao, N Li, L Ma, X Xia, X Zhang, N Ding, N Li 2021 International Conference on High Performance Big Data and Intelligent …, 2021 | 12 | 2021 |
| Identification of susceptibility SNPs in CTLA-4 and PTPN22 for scleritis in Han Chinese F Li, X Ma, L Du, L Shi, Q Cao, N Li, T Pang, Y Liu, A Kijlstra, P Yang Clinical & Experimental Immunology 197 (2), 230-236, 2019 | 12 | 2019 |
