Title: Biometric Recognition in the Era of AI Generated Content (AIGC)
Speaker: Prof. Dr. Xiaoming Liu, Michigan State University
When: April 24, 2024 at 10 am EST (4:00 pm CEST, 7 am PST, 10 pm Beijing Time)
Where: Online (Zoom)
Recording of the Webinar
Abstract
In recent years we have witnessed impressive progress on AIGC (Artificial Intelligence Generated Content). AIGC has many applications in our society, as well as benefits diverse computer vision tasks. In the context of biometric recognition, we believe that the AIGC era calls for innovation on both data generation and how to leverage the generated data. In this talk, I will present a number of efforts that showcases these innovations, including: 1) how to bridge the gap between the training data distribution and test data distribution; 2) how to generate a complete synthetic database to train face recognition models; 3) how to estimate the 3D body shape from an image of clothed human body; and 4) how to manipulate a human body image by changing its body pose, clothing style, background, and identity. In the end, we will briefly overview other research efforts in the Computer Vision Lab at Michigan State University.
About The Speaker
Dr. Xiaoming Liu is the MSU Foundation Professor, and Anil and Nandita Jain Endowed Professor at the Department of Computer Science and Engineering of Michigan State University (MSU). He is also a visiting 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 Global Research. He works on computer vision, machine learning, and biometrics, especially on face related analysis and 3D vision. Since 2012, he helps to develop a strong computer vision area in MSU, who is ranked top 15 in US according to csrankings.org. He is an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence. He has authored more than 200 publications and has filed 35 patents. His work has been cited over 25000 times with an H-index of 76. He is a fellow of IEEE and IAPR.
