Research area: Computer Vision (CV), Pattern Recognition (PR), Machine Learning (ML), Face Recognition (FR)
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. After graduate, 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 (deep learning). He especially focuses on face recognition related research topics, and machine learning with little data or weakly-supervised data. He has published more than 200 papers in refereed journals and proceedings in the areas of computer vision and pattern recognition. He has served as Area Chair for many international conferences including ICCV11, ICPR12, ACCV12, FG13, ICPR14, ICASSP14, ACCV16, ACCV18, FG18, and BTAS18. 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 personally interested in brain science, cognitive neuroscience, as well as their interdisciplinary researche topics with AI.
My team focuses on new machine learning methods for scenarios with complex data conditions, especially little data, wealy-labeled data, semi-supervised data, incomplete data, where new models and new optimizing methodsareneeded to design. In terms of methodology, we are interested in transfer learning, meta-learning, and knowledge-guided learning.
My team is interested in everything on face perception, 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, 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 or possibly here: https://xue.glgoo.com/citations?user=Vkzd7MIAAAAJ&hl=zh-CN&oi=ao or here: 【pdf】