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assistant professor li, nannan

school of computer science and engineering, faculty of innovation engineering

macau university of science and technology

office: a302

tel.: 853-8897 3039

e-mail:

• ph.d. in pattern recognition and intelligent systems, university of chinese academy of sciences, china, 2015.
• m.s. in opto-electronic engineering, hefei university of technology, china, 2011.
• b.s. in optical information science and technology, hefei university of technology, china, 2008.

• digital image processing

• deep learning
• computer vision
• multi-modal learning

• mar 2021 - present assistant professor, international institute for next generation internet, macau university of science and technology, macau.
• mar 2018 - mar 2021 director of computer vision r&d, longgang institutes of intelligent video and audio technology, china.
• oct 2015 - oct 2018 postdoctoral fellow, school of electronic and computer engineering, peking university, china.

1. jingjia huang, nannan li, thomas li, shan liu and ge li, "spatial-temporal context-aware online action detection and prediction", ieee transactions on circuits and systems for video technology (t-csvt), 2019.
2. nannan li, jingjia huang, thomas li, huiwen guo and ge li, "detecting action tubes via spatial action estimation and temporal path inference,", neurocomputing, 2018.
3. nannan li, huiwen guo, yang zhao, thomas li and ge li, "active temporal action localization in untrimmed videos based on deep reinforcement learning," ieee access, 2018.
4. nannan li, xinyu wu, dan xu, huiwen guo and wei feng, "spatio-temporal context analysis within video volumes for anomalous-event detection and localization," neurocomputing, 2015.
5. nannan li, xinyu wu, huiwen guo, dan xu and yen-lun chen, " anomaly detection in video surveillance via gaussian process", international journal of pattern recognition and artificial intelligence, 2015.
6. dan xu, rui song, xinyu wu, nannan li, wei feng and huihuan qian, "video anomaly detection based on a hierarchical activity discovery within spatio-temporal contexts", neurocomputing, 2014.
7. jia-xing zhong, nannan li, weijie kong, shan liu, thomas h.li, and ge li, ""graph convolutional label noise cleaner: train a plug-and-play action classifier for anomaly detection"", international conference on computer vision and pattern recognition (cvpr), 2019."
8. jingjia huang, zhangheng li, nannan li, shan liu and ge li, "attpool: towards hierarchical feature representation in graph convolutional networks via attention mechanism", international conference on computer vision (iccv), 2019.
9. jingjia huang, nannan li, tao zhang, ge li, tiejun huang, wen gao, "sap: self-adaptive proposal model for temporal action detection based on reinforcement learning," in aaai conference on artificial intelligence (aaai), 2018.
10. jingjia huang, nannan li, jiaxing zhong, thomas li, and ge li, "online action tube detection via resolving the spatio-temporal context pattern", acm multimedia, 2018.
11. jiaxing zhong, nannan li, weijie kong, tao zhang, thomas li and ge li, "step-by-step erasion, one-by-one collection: a weakly supervised temporal action detector", acm multimedia, 2018.
12. jingjia huang, ge li, nannan li, ronggang wang, and wenmin wang, "a violence detection approach based on spatio-temporal hypergraph transition", international conference on computer analysis of images and patterns, 2017.
13. nannan li, dan xu, zhenqiang ying, zhihao li, and ge li, "searching action proposals via spatial actionness estimation and temporal path inference and tracking", asian conference on computer vision (accv), 2016.
14. zhihao li, wenmin wang, nannan li, jinzhuo wang, "tube convnets: better exploiting motion for action recognition," international conference on image processing (icip), 2016.
15. nannan li, huiwen guo, dan xu, xinyu wu, "multi-scale analysis of contextual information within spatio-temporal video volumes for anomaly detection", international conference on image processing (icip), 2014.
16. dan xu, xinyu wu, dezhen song, nannan li, yen-lun chen, "hierarchical activity discovery within sspatio-temporal context for video anomaly detection", international conference on image processing (icip), 2013.