On the morning of April 29 at 11:00, our institute invited Dr. Xiaoming Liu from Michigan State University to give an academic report titled “Visual Recognition in the Era of Foundation Models.”
Abstract:
Visual recognition aims to recognize objects, or their instances given an imagery. This is one of the most fundamental tasks that computer vision researchers are striving to solve in the past decades. With the recent emerging of large foundation models, being LLM or VLM, researchers are actively studying how to advance visual recognition in the era of foundation models. Some common questions include 1) how to leverage pre-trained foundation models for visual recognition? 2) how to continue the innovation of vision transformer in light of downstream tasks? 3) how to design and learn our own foundation model for a specific task? This talk will shed some lights on how we have been answering these questions in recent years. I will also share some of our recent works on 3D vision and anti-deepfakes.
Speaker Introduction:
Dr. Xiaoming Liu is currently an MSU Foundation Professor and the Anil and Nandita Jain Endowed Professor in the Department of Computer Science and Engineering at Michigan State University (MSU). He received his Ph.D. from Carnegie Mellon University in 2004. Prior to joining MSU in 2012, he was a research scientist at General Electric (GE) Global Research. His research interests span computer vision, machine learning, and biometrics, with a particular focus on face-related analysis and 3D vision. Since 2012, Dr. Liu has helped build a highly competitive computer vision program at MSU, which now ranks among the top 15 in the United States according to five-year statistics from csrankings.org. He will serve as a Program Co-Chair for CVPR 2028 and is an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Dr. Liu has published over 200 academic papers and filed 35 U.S. patent applications. His research has been cited more than 30,000 times on Google Scholar, with an h-index of 81. He is a Fellow of both the Institute of Electrical and Electronics Engineers (IEEE) and the International Association for Pattern Recognition (IAPR).
