Abstract: Future robots, intelligent vehicles, and smart spaces will require a deep and accurate understanding of the environment under diverse and challenging conditions, advanced reasoning capabilities and robust planning under uncertainty. In particular, understanding behaviors of people, such as drivers, road occupants or users interacting with smart machines will be critical for safety, contextualized assistance and natural interfaces. In this talk, I will give an overview of our recent work in computer vision for visual understanding of human actions and behaviors. Our approach extends recent advances in deep learning to enable learning with weak supervision, detecting human actions in videos at scale and anticipating events before they occur.

Bio: Juan Carlos Niebles received an Engineering degree in Electronics from Universidad del Norte (Colombia) in 2002, an M.Sc. degree in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign in 2007, and a Ph.D. degree in Electrical Engineering from Princeton University in 2011. He is a Senior Research Scientist at the Stanford AI Lab and Associate Director of Research at the Stanford-Toyota Center for AI Research since 2015. He is also an Assistant Professor of Electrical and Electronic Engineering in Universidad del Norte (Colombia) since 2011. His research interests are in computer vision and machine learning, with a focus on visual recognition and understanding of human actions and activities, objects, scenes, and events. He is a recipient of a Google Faculty Research award (2015), the Microsoft Research Faculty Fellowship (2012), a Google Research award (2011) and a Fulbright Fellowship (2005).