Keynote Speakers

Topic 1:

Deep Metric Learning for Visual Content Understanding

Jiwen Lu

Associate Professor of Department of Automation
Tsinghua University, China

Abstract: In this talk, I will overview the trend of deep metric learning techniques and discuss how they are employed to boost the performance of various visual content understanding tasks. Specifically, I will introduce some of our proposed deep metric learning methods including discriminative deep metric learning, deep localized metric learning, deep coupled metric learning, multi-manifold deep metric learning, deep transfer metric learning, deep adversarial metric learning, and multi-view deep metric learning, which are developed for different application-specific visual content understanding tasks such as face recognition, person re-identification, object recognition, action recognition, visual tracking, image set classification, and visual search. Lastly, I will discuss some open problems in deep metric learning to show how to further develop more advanced deep metric learning methods in the future.


Biography: Jiwen Lu is currently an Associate Professor with the Department of Automation, Tsinghua University, China. His current research interests include computer vision, pattern recognition, and multimedia computing. He has authored/co-authored over 200 scientific papers in these areas, where 70 of them are PAMI/IJCV/CVPR/ICCV/ECCV papers. He was/is a member of the Multimedia Signal Processing Technical Committee and the Information Forensics and Security Technical Committee of the IEEE Signal Processing Society, and the Multimedia Systems and Applications Technical Committee and the Visual Signal Processing and Communications Technical Committee of the IEEE Circuits and Systems Society, respectively. He serves as the Co-Editor-of-Chief for Pattern Recognition Letters, an Associate Editor for IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Biometrics, Behavior, and Identity Sciences, Pattern Recognition, and Journal of the Visual Communications and Image Representation. He was/is the Program Co-Chair of IEEE ICME’2020 and IEEE AVSS’2020, and an Area Chair for CVPR 2020/2021, ICME’2015/2017-2019, ICIP’2017-2019, ICPR 2018, and ICB 2015/2016. He was a recipient of the National 1000 Young Talents Program of China in 2015, the National Science Fund of China Award for Excellent Young Scholars in 2018, the Best Platinum Paper Award of ICME’ 2018, the Multimedia Rising Star Award of IEEE ICME’2019.

Topic 2:

Challenges in AI Security

Dapeng Oliver Wu

Fellow, IEEE

Professor of Department of Electrical & Computer Engineering
University of Florida, USA

Abstract: With the recent breakthroughs, artificial intelligence, especially deep neural networks, is pervasively serving numerous areas such as healthcare, autonomous driving, and Internet of things. Deep neural networks are capable of making accurate predictions and reasonably good decisions but their predictions or decisions are not explicitly explainable. In particular, major security and privacy concerns exist in deep neural networks.

  In this talk, I will first provide an overview of trustworthy deep neural networks and then focus on our recent research on a data-agnostic model stealing attack. The talk will conclude by discussing future research directions in security and privacy concerns and potential countermeasures in deep neural networks.


Biography: Dapeng Oliver Wu received Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, PA, in 2003. Since 2003, he has been on the faculty of Electrical and Computer Engineering Department at University of Florida, Gainesville, FL, where he is currently Professor. His research interests are in the areas of networking, communications, video coding, image processing, computer vision, signal processing, and machine learning.

  He received University of Florida Term Professorship Award in 2017, University of Florida Research Foundation Professorship Award in 2009, AFOSR Young Investigator Program (YIP) Award in 2009, ONR Young Investigator Program (YIP) Award in 2008, NSF CAREER award in 2007, the IEEE Circuits and Systems for Video Technology (CSVT) Transactions Best Paper Award for Year 2001, the Best Paper Award in GLOBECOM 2011, and the Best Paper Award in QShine 2006.

  Currently, he serves as Editor-in-Chief of IEEE Transactions on Network Science and Engineering. He was the founding Editor-in-Chief of Journal of Advances in Multimedia between 2006 and 2008, and an Associate Editor for IEEE Transactions on Communications, IEEE Transactions on Signal and Information Processing over Networks, IEEE Signal Processing Magazine, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Wireless Communications and IEEE Transactions on Vehicular Technology. He has served as Technical Program Committee (TPC) Chair for IEEE INFOCOM 2012. He was elected as a Distinguished Lecturer by IEEE Vehicular Technology Society in 2016. He is an IEEE Fellow.


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