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Stan Z. LI, Ph.D.
School of Engineering
AI Research and Innovation Laboratory
“My goal is to achieve world-class excellence in research and student training and build a great Westlake University.”
Stan Z. Li, IEEE Fellow. He received his Ph.D. degree from Surrey University, UK, in 1991. He was awarded Honorary Doctorate of Oulu University, Finland, in 2013. He was the director of the Center for Biometrics and Security Research (CBSR) , Chinese Academy of Sciences, 2004~2019. He worked at Microsoft Research Asia as a Research Lead, 2000~2004. Prior to that, he was an associate professor (tenure) at Nanyang Technological University, Singapore. He joined Westlake University as a Chair Professor of Artificial Intelligence in February, 2019. His current interests include fundamental research in machine learning, data science, and applied research in multiple AI-related interdisciplinary fields (computer vision, smart sensors, life science, material science, and environmental science).
Stan Z. Li has published over 400 papers in international journals and conferences, authored, and edited 9 books, with over 40,000 Google Scholar citations. Among these are Markov Random Field Models in Image Analysis (Springer), Handbook of Face Recognition (Springer) and Encyclopedia of Biometrics (Springer). He served as an associate editor of IEEE Transactions on Pattern Analysis and Machine Intelligence and organized more than 100 international conferences or workshops among which he was a co-chair of International (Joint) Conference on Biometrics for 2007, 2009, 2013, 2014, 2015, 2016, and 2018.
Stan Z. Li is an expert in face recognition, biometrics, and intelligent video surveillance. The EyeCU face recognition system he developed at Microsoft Research Asia was demonstrated by Bill Gate during a CNN interview. He has been leading several national and international projects in biometrics and intelligent video surveillance. The AuthenMetric face recognition system and intelligent video surveillance system have been deployed in several national projects, including Beijing 2008 Olympic Games, Shanghai 2010 World Expo, and immigration control at China borders. He is a co-chair of SAC/TC100/SC2 for biometrics standardization in China and delivered a plenary speech on Biometrics in China at ISO/IEC JTC1/SC37 on behalf of the China National Body.
Representative Publications by Google Scholar
1. Stan. Z. Li. Markov Random Field Modeling in Image Analysis (3rd Edition). Springer. 2011.
2. Stan Z. Li and Anil K. Jain (eds). Handbook of Face Recognition (2nd Edition). Springer, 2011.
3. Stan Z. Li and Anil K. Jain (eds). Encyclopedia of Biometrics. Springer, 2015.
4. SZ Li, ZQ Zhang. Floatboost learning and statistical face detection. IEEE Transactions on pattern analysis and machine intelligence 26 (9), 1112-1123. 2004.
5. SZ Li, RF Chu, SC Liao, L Zhang. Illumination invariant face recognition using near-infrared images. IEEE Transactions on pattern analysis and machine intelligence, 29 (4), 627-639. 2007.
6. SZ Li, J Lu. Face recognition using the nearest feature line method. IEEE transactions on neural networks 10 (2), 439-443. 1999.
7. SZ Li, Face recognition based on nearest linear combinations. Proc. of CVPR, pp.839-844 June 1998
8. SZ Li, L Zhu, ZQ Zhang, A Blake, HJ Zhang, H Shum. Statistical learning of multi-view face detection. ECCV,2002.
9. SZ Li, XW Hou, HJ Zhang, QS Cheng. Learning spatially localized, parts-based representation. CVPR 2001.
10. S Liao, Y Hu, X Zhu, SZ Li. Person re-identification by local maximal occurrence representation and metric learning. CVPR 2015.
11. D Yi, Z Lei, S Liao, SZ Li. Deep metric learning for person re-identification. ICPR 2014.
12. D Yi, Z Lei, S Liao, SZ Li. Learning face representation from scratch. arXiv:1411.7923. 2014.
13. S Liao, X Zhu, Z Lei, L Zhang, SZ Li. Learning multi-scale block local binary patterns for face recognition. ICB 2007.
14. D Yi, Z Lei, S Liao, SZ Li. Deep metric learning for person re-identification. 22nd International Conference on Pattern Recognition, 34-39，2014.
15. G Guo, SZ Li, K Chan. Face recognition by support vector machines. FG 2000.
1. Zichang Tan，Yang Yang，Jun Wan，Guodong Guo，Stan Z. Li Relation Aware Pedestrian Attribute Recognition with Graph Convolutional Networks 34th Association for the Advance of Artificial Intelligence .
2. Guo J, Zhu X, Zhao C, et al. Learning Meta Face Recognition in Unseen Domains[J]. arXiv preprint arXiv:2003.07733, 2020.
3. Li A, Tan Z, Li X, et al. CASIA-SURF CeFA: A Benchmark for Multi-modal Cross-ethnicity Face Anti-spoofing[J]. arXiv preprint arXiv:2003.05136, 2020.
4. Zhang S, Liu A, Wan J, et al. Casia-surf: A large-scale multi-modal benchmark for face anti-spoofing[J]. IEEE Transactions on Biometrics, Behavior, and Identity Science, 2020, 2(2): 182-193.
1. Zhang S, Chi C, Yao Y, et al. Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection[J]. arXiv preprint arXiv:1912.02424, 2019.
2. Liu A, Tan Z, Li X, et al. Static and Dynamic Fusion for Multi-modal Cross-ethnicity Face Anti-spoofing[J]. arXiv preprint arXiv:1912.02340, 2019.
3. Zhang S, Wang X, Lei Z, et al. Faceboxes: A CPU real-time and accurate unconstrained face detector[J]. Neurocomputing, 2019, 364: 297-309.
4. Yuan Q, Wan J, Lin C, et al. Global and Local Spatial-Attention Network for Isolated Gesture Recognition[C]//Chinese Conference on Biometric Recognition. Springer, Cham, 2019: 84-93.
5. Chi C, Zhang S, Xing J, et al. Relational Learning for Joint Head and Human Detection[J]. arXiv preprint arXiv:1909.10674, 2019.
6. Xiao J, Tang Y, Guo J, et al. 3DMA: A Multi-modality 3D Mask Face Anti-spoofing Database[C]//2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). IEEE, 2019: 1-8.
7. Chi C, Zhang S, Xing J, et al. PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes[J]. arXiv preprint arXiv:1909.06826, 2019.
8. Zhang S, Chi C, Lei Z, et al. RefineFace: Refinement Neural Network for High Performance Face Detection[J]. arXiv preprint arXiv:1909.04376, 2019.
9. Tan Z, Yang Y, Wan J, et al. Deeply-learned hybrid representations for facial age estimation[C]//Proceedings of the 28th International Joint Conference on Artificial Intelligence. AAAI Press, 2019: 3548-3554.
10. Wan J, Lin C, Wen L, et al. ChaLearn Looking at People: IsoGD and ConGD Large-scale RGB-D Gesture Recognition[J]. arXiv preprint arXiv:1907.12193, 2019.
11. Chi C, Zhang S, Xing J, et al. Selective refinement network for high performance face detection[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2019, 33: 8231-8238.
12. Zhang S, Xie Y, Wan J, et al. WiderPerson: A Diverse Dataset for Dense Pedestrian Detection in the Wild[J]. IEEE Transactions on Multimedia, 2019.
13. Wu J, Liao S, Wang X, et al. Clustering and dynamic sampling based unsupervised domain adaptation for person re-identification[C]//2019 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2019: 886-891.
14. Tan Z, Yang Y, Wan J, et al. Attention-Based Pedestrian Attribute Analysis[J]. IEEE transactions on image processing, 2019, 28(12): 6126-6140.
15. Chen H, Hu G, Lei Z, et al. Attention-Based Two-Stream Convolutional Networks for Face Spoofing Detection[J]. IEEE Transactions on Information Forensics and Security, 2019, 15: 578-593.
16. Lin X, Wan J, Xie Y, et al. Task-Oriented Feature-Fused Network With Multivariate Dataset for Joint Face Analysis[J]. IEEE transactions on cybernetics, 2019.
17. Yang Y, Lei Z, Wang J, et al. In Defense of Color Names for Small-Scale Person Re-Identification[C]//2019 International Conference on Biometrics (ICB). IEEE, 2019: 1-6.
18. Jin H, Zhang S, Zhu X, et al. Learning Lightweight Face Detector with Knowledge Distillation[C]//2019 International Conference on Biometrics (ICB). IEEE, 2019: 1-7.
19. Zhang S, Wen L, Shi H, et al. Single-shot scale-aware network for real-time face detection[J]. International Journal of Computer Vision, 2019, 127(6-7): 537-559.
20. Zhu X, Liu H, Lei Z, et al. Large-scale bisample learning on id versus spot face recognition[J]. International Journal of Computer Vision, 2019, 127(6-7): 684-700.
21. Lin X, Liang Y, Wan J, et al. Region-Based Context Enhanced Network for Robust Multiple Face Alignment[J]. IEEE Transactions on Multimedia, 2019, 21(12): 3053-3067.
22. Wang X, Lei Z, Guo X, et al. Multi-view subspace clustering with intactness-aware similarity[J]. Pattern Recognition, 2019, 88: 50-63.
23. Loy C C, Lin D, Ouyang W, et al. WIDER face and pedestrian challenge 2018: Methods and results[J]. arXiv preprint arXiv:1902.06854, 2019.
24. Zhang L, Ding X, Ma Y, et al. Electronic Health Record Phenotyping with Internally Assessable Performance (PhIAP) using Anchor-Positive and Unlabeled Patients[J]. arXiv preprint arXiv:1902.10060, 2019.
25. Zhang S, Zhu R, Wang X, et al. Improved selective refinement network for face detection[J]. arXiv preprint arXiv:1901.06651, 2019.
26. Guo J, Zhu X, Xiao J, et al. Improving Face Anti-Spoofing by 3D Virtual Synthesis[J]. arXiv preprint arXiv:1901.00488, 2019.
27. Wu J, Yang Y, Liu H, et al. Unsupervised Graph Association for Person Re-Identification[C]//Proceedings of the IEEE International Conference on Computer Vision. 2019: 8321-8330.
28. Zhuang C, Zhang S, Zhu X, et al. FLDet: A CPU Real-time Joint Face and Landmark Detector[C]//IAPR International Conference on Biometrics (ICB). Crete, Greece. 2019.
29. Liu H, Zhu X, Lei Z, et al. Adaptiveface: Adaptive margin and sampling for face recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 11947-11956.
30. Liu A, Wan J, Escalera S, et al. Multi-modal face anti-spoofing attack detection challenge at cvpr2019[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2019: 0-0.
31. Zhang S, Wang X, Liu A, et al. A dataset and benchmark for large-scale multi-modal face anti-spoofing[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 919-928.
1. Xiangyu Zhu, Xiaoming Liu, Zhen Lei, Stan Z. Li, "Face Alignment In Full Pose Range: A 3D Total Solution", IEEE Transaction on Pattern Analysis and Machine Intelligence (Accepted).
2. Hailin Shi, Xiangyu Zhu, Shengcai Liao, Zhen Lei, Stan Z. Li. “Ensemble Deep Network for Face Recognition in the Wild”, IEEE Transaction on Intelligent Systems (IS) (Accepted)
3. Shifeng Zhang, Xiangyu Zhu, Zhen Lei, Xiaobo Wang, Hailin Shi, Stan Z. Li, "Detecting Face with Densely Connected Face Proposal Network," in Neurocomputing, Volume 284, Pages 119-127, 5 April 2018.
4. Zichang Tan, Jun Wan, Zhen Lei, Ruicong Zhi, Guodong Guo, Stan Z. Li, "Efficient Group-n Encoding and Decoding for Facial Age Estimation", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 40, No. 11, 2018.
5. Shifeng Zhang, Longyin Wen, Xiao Bian, Zhen Lei, Stan Z. Li. “Occlusion-aware R-CNN: Detecting Pedestrians in a Crowd”. In Proceedings of European Conference on Computer Vision, (ECCV2018). Munich, Germany, September 8-14, 2018.
6. Xiaobo Wang, Zhen Lei, Shengcai Liao, Xiaojie Guo, Yang Yang, Stan Z. Li, “Dependence-Aware Feature Coding for Person Re-Identification”, IEEE Signal Processing Letters, vol 25, no. 4, pp.506-510, 2018.
7. Jun Wan, Zichang Tan, Zhen Lei, Guodong Guo, Stan Z. Li, "Auxiliary Demographic Information Assisted Age Estimation with Cascaded Structure", IEEE Transactions on Cybernetics, Vol 48, No. 9, pp. 2531-2541, 2018.
8. Jianzhu Guo, Xiangyu Zhu, Zhen Lei, Stan Z. Li. “Face Synthesis for Eyeglasss-Robust Face Recognition”. In Proceedings of the 13th Chinese Conference on Biometrics, (CCBR2018). XinJiang, China, August 11-12, 2018.
9. Chubin Zhuang, Shifeng Zhang, Xiangyu Zhu, Zhen Lei, Stan Z. Li. “Single Shot Attention-Based Face Detector”. In Proceedings of the 13th Chinese Conference on Biometrics, (CCBR2018). XinJiang, China, August 11-12, 2018.
10. Xiaobo Wang, Zhen Lei, Hailin Shi, Xiaojie Guo, Xiangyu Zhu, Stan Z. Li. “Co-Referenced Subspace Clustering”. In Proceedings of IEEE International Conference on Multimedia and Expo, San Diego, USA, July 23-27, 2018.
11. Xiaobo Wang, Shifeng Zhang, Zhen Lei, Si Liu, Xiaojie Guo, Stan Z. Li. “Ensemble Soft-Margin Softmax Loss for Image Classification”. In Proceedings of the 27th International Joint Conference on Artificial Intelligence, (IJCAI-2018), Stockholm, Sweden, July 13-19, 2018.
12. Shifeng Zhang, Longyin Wen, Xiao Bian, Zhen Lei, Stan Z. Li. “Single-Shot Refinement Neural Network for Object Detection”. In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, (CVPR2018). Salt Lake City, Utah, June 18-22, 2018.
13. Jinlin Wu, Hailin Shi, Shu Zhang, Zhen Lei, Yang Yang, Stan Z. Li, "De-mark GAN: Removing DenseWatermarkWith Generative Adversarial Network". In Proceedings of the 11th IAPR International Conference on Biometrics (ICB2018). Queensland, Australia, Feb. 20-23, 2018.
14. Lipeng Wan, Jun Wan, Yi Jin, Zichang Tan, Stan Z.Li, "Fine-grained Multi-attribute Adversarial Learning for Face Generation of Age, Gender and Ethnicity". In Proceedings of the 11th IAPR International Conference on Biometrics (ICB2018). Queensland, Australia, Feb. 20-23, 2018.
15. Chi Lin, Jun Wan, Yanyan Liang, Stan Z. Li, "Large-scale Isolated Gesture Recognition Using Masked Res-C3D Network and Skeleton LSTM", In Proceedings of the 13th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2018) , 2018.
16. Yang-Yu Fan, Shu Liu, Bo Li, Zhe Guo, Ashok Samal, Jun Wan, Stan Z. Li, "Label Distribution-Based Facial Attractiveness Computation by Deep Residual Learning", IEEE Transactions on Multimedia, Vol 20, No, 8, pp. 2196-2208, 2018.