Visual perception of the scene and identification of individuals are conventional tasks of the AVSS community. In the deep learning era, many new research thrusts are being developed for these conventional tasks. In this talk, we will share two thrusts based on the research conducted at the Computer Vision Lab at Michigan State University. The first is the 3D perception, i.e., detection, tracking and forecasting moving objects in the 3D space. While most of existing 3D perception algorithms rely on depth sensors such as LiDAR, we will start with our monocular 3D perception works, and then discuss the new sensing capability enabled when fusing with additional radar or LiDAR sensors. The second is trustworthy biometrics. In recent years we have witnessed increasing application scenarios of biometrics systems in our daily life, despite the societal concerns on some of the weakness of the technology. To address these concerns, trustworthy biometrics has become an emerging research thrust. Specifically, we will discuss various topics such as biometrics security (e.g., presentation attack detection and forgery detection), biasness in biometrics, adversarial robustness, and interpretable biometrics.
Dr. Xiaoming Liu is the MSU Foundation Professor at the Department of Computer Science and Engineering of Michigan State University (MSU) and also a visiting research scientist at Google Research. He received Ph.D. degree from Carnegie Mellon University in 2004. Before joining MSU in 2012 he was a research scientist at General Electric (GE) Global Research. He works on computer vision, machine learning, and biometrics especially on 3D vision, and face related analysis. Since 2012 he helps to develop a strong computer vision area in MSU who is ranked top 15 in US according to the 5-year statistics at csrankings.org. He received the 2018 Withrow Distinguished Scholar Award from MSU. He has been Area Chairs for numerous conferences, including CVPR, ICCV, ECCV, ICLR, NeurIPS, ICML, the Co-Program Chair of BTAS’18, WACV’18, IJCB’22 and AVSS’22 conferences, and Co-General Chair of FG’23 conference. He is an Associate Editor of Pattern Recognition and IEEE Transaction on Image Processing. He has authored more than 160 scientific publications, and has filed 29 U.S. patents. His work has been cited over 15000 times according to Google Scholar, with an H-index of 60. He is a fellow of International Association for Pattern Recognition (IAPR). His research has been widely reported in prominent national and international news outlets including the Wall Street Journal, CNBC, CNET, Engadget, Fortune, the Mac Observer, MSU Today, New Scientist, Silicon Angle, VentureBeat, and the Verge. More information of Dr. Liu’s research can be found at http://cvlab.cse.msu.edu