3D Visual Character Motion Generation, Reconstruction, and Embodied Agents

Abstract

Recent advancements in sensing and deep learning have unlocked exciting possibilities for the visual analysis of human and animal motions in the physical 3D space. These innovations hold great potential for applications across diverse domains, including for example natural user interfaces, AR/VR, robotics, and gaming. In this talk, I will present the latest research progress in this rapidly evolving field including especially 3D human motion generation, pose tracking and shape reconstruction, and related tasks - highlighting key developments from the past few years as well as contributions from our own work.

Bio

Li CHENG is a full professor with the Department of Electrical and Computer Engineering, University of Alberta. He is currently an associate editor of IEEE Transactions on Image Processing. Prior to joining University of Alberta, he worked at A*STAR, Singapore, TTI-Chicago, USA, and NICTA, Australia. His current research interests include computer vision, multimedia data analytics, and applications. He has over 200 papers in peer-reviewed journals and conferences. His papers have been nominated for Best Paper Award at CVPR 2021. More recent details can be found at his lab website, https://vision-and-learning-lab-ualberta.github.io/.