Grainger College of Engineering, All Events

Abstract: Generative models have empowered human creators to visualize their imaginations without artistic skills and labor. A prominent example is large-scale text-to-image/video generation models. However, these models are often difficult to control and do not respect 3D perspective geometry and the temporal consistency of videos. In this talk, I will showcase several of our recent efforts to improve controllability for visual imagination. Specifically, I will discuss how we enable semantic and spatial control for 2D image generation, facilitate layered decompositions for video editing, and synthesize object and camera motions from monocular videos.

Biography: Jia-Bin Huang is a Capital One-endowed Associate Professor of Computer Science at the University of Maryland, College Park. Before coming to UMD, Huang was a research scientist at Meta Reality Labs and an Assistant Professor of Electrical and Computer Engineering at Virginia Tech. Huang received his Ph.D. from the University of Illinois, Urbana-Champaign (UIUC) in 2016. His research interests include 3D computer vision, generative models, and computational photography. Huang is the recipient of the Thomas & Margaret Huang Award, NSF CRII award, faculty award from Samsung, Google, 3M, Qualcomm, Meta, and a Google Research Scholar Award.