Department of Electrical and Computer Engineering
Co-Director, Cross Pacific AI Initiative of UW
University of Washington, Seattle, WA, USA

Prof. Jenq-Neng Hwang

"Human Motion Understanding and Generation"

Abstract

  Human motion analysis via human pose estimation in both 2D and 3D remains a fundamental yet challenging problem in computer vision. On the other hand, it has broad applications in action recognition, human-computer interaction, motion analysis, and object tracking. Despite recent advances, achieving robustness and efficiency in real-world and edge-device scenarios remains difficult. This talk will first review perceptual AI techniques for human motion understanding, based on 2D/3D human pose estimation, and generative AI techniques for human motion generation based on a novel diffusion-based framework for joint motion and text generation via mutual prompting. Several practical applications of these techniques will also be discussed.

Biography

  Dr. Jenq-Neng Hwang received the BS and MS degrees, both in electrical engineering from the National Taiwan University, Taipei, Taiwan, in 1981 and 1983 separately. He then received his Ph.D. degree from the University of Southern California. In the summer of 1989, Dr. Hwang joined the Department of Electrical and Computer Engineering (ECE) of the University of Washington in Seattle, where he has been promoted to Full Professor since 1999. He served as the Associate Chair for Research from 2003 to 2005, and from 2011-2015. He also served as the Associate Chair for Global Affairs from 2015-2020. He is currently the International Programs Lead in the ECE Department. Currently, he serves as the Co-Director of Cross-Pacific AI Initiative (X-PAI) in the College of Engineering (CoE), UW. He is the Founder and Director of the Information Processing Lab., which has won several AI City Challenges awards in the past years. He has written more than 450 journal, conference papers and book chapters in the areas of machine learning, multimedia signal processing, computer vision, and multimedia system integration and networking (my Google citation), including an authored textbook on "Multimedia Networking: from Theory to Practice," published by Cambridge University Press. Dr. Hwang has close working relationship with the industry on artificial intelligence and machine learning.

  Dr. Hwang received the 1995 IEEE Signal Processing Society's Best Journal Paper Award. He is a founding member of Multimedia Signal Processing Technical Committee of IEEE Signal Processing Society and was the Society's representative to IEEE Neural Network Council from 1996 to 2000. He is currently a member of Multimedia Technical Committee (MMTC) of IEEE Communication Society and also a member of Multimedia Signal Processing Technical Committee (MMSP TC) of IEEE Signal Processing Society. He served as associate editors for IEEE T-SP, T-NN and T-CSVT, T-IP and Signal Processing Magazine (SPM). He served as the General Co-Chair of 2021 and 2022 IEEE World AI IoT Congress, Seattle, WA. He also served as the Program Co-Chair of IEEE ICME 2016 and was the Program Co-Chairs of ICASSP 1998 and ISCAS 2009. Dr. Hwang is a fellow of IEEE since 2001.