职 称：研究员 (Professor)
电子邮箱：Email: sgshan at ict dot ac dot cn
通讯地址：北京市海淀区科学院南路6号(Add.: 6 Kexueyuannan Road, Beijing, 100190, China)
研究方向：CV, PR, ML
Shiguang Shan received M.S. degree in computer science from the Harbin Institute of Technology, Harbin, China, in 1999, and Ph.D. degree in computer science from the Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), Beijing, China, in 2004. He joined ICT, CAS in 2002 and became a full Professor in 2010. He is now the deputy director of the Key Lab of Intelligent Information Processing of CAS.
His research interests cover computer vision, pattern recognition, and machine learning. He especially focuses on computational face perception related research topics, and machine learning with data of limited supervision. He has published more than 300 papers in refereed journals and proceedings. He has served as Area Chair (or Senior PC) for many international conferences including CVPR19/20/21, AAAI20/21, IJCAI21, ICPR12/14/20, ACCV12/16/18, FG13/18/20, BTAS18, ICASSP14, and ICCV11. He is(/was) Associate Editors of several international journals including IEEE Trans. on Image Processing, Computer Vision and Image Understanding, Neurocomputing, and Pattern Recognition Letters. He is a recipient of the China’s State Natural Science Award in 2015, and the China’s State S&T Progress Award in 2005 for his research work.
He is also the co-founder and rotating Chairman of Steering Committee of VALSE (Vision And Learning SEminar), a China-based non-official scholarly community. VALSE holds annual conference every year since 2011, and has held more than 220 times of Webinar (online seminar) since 2014. Numerous Chinese researchers and students have benefitted from these VALSE events. Taking VALSE Annual Conference 2019 as an example, more than 5,000 audiences attended this event held in Hefei China.
He is also personally interested in brain science, cognitive neuroscience, as well as their interdisciplinary researche topics with AI.
My ORCID: https://orcid.org/0000-0002-8348-392X
My Google scholar: https://scholar.google.com/citations?user=Vkzd7MIAAAAJ
My team focuses on new machine learning methods for scenarios with complex data conditions, especially small data, wealy-labeled data, semi-supervised data, incomplete data, where new models and new optimizing methodsareneeded to design. In terms of methodology, I am interested in self-supervised learning, transfer learning, meta-learning, and knowledge-guided learning.
My team is interested in all kinds of vision tasks from face recognition to human understanding, including (but not limited to) face detection and tracking, facial landmark locating, face alignment, face identification, face verification, face retrieval, expression recognition, facial attribute estimation, 3D face reconstruction, face parsing, lip reading, heart rate estimation, engagement estimation, gaze tracking, etc. We have broad cooperation with industrial parters, including Huawei, Ping'an, Qualcomm, China Mobile, Baidu, Isvision, Samsung, Omron, Panasonic, etc. Especially, our face recognition technology has been used on Huawei smart phone and Huawei Cloud album.
My team is also interested in generic object detection, segmentation, and recognition, especially pedestrian detection and tracking, human pose estimation and body segmentation, vehicle detection and tracking, human and vehicle re-identification etc. These technologies are applied to video surveillance.
1. Please kindly refer to my Google scholar homepage： https://scholar.google.com/citations?user=Vkzd7MIAAAAJ&hl=zh-CN 【pdf】