Abstract

Despite recent progress, AI is still far from understanding the physics of the world, and there is a large gap between the abilities of humans and the state-of-the-art AI methods. In this talk, I will focus on physics-based scene understanding and interactive visual reasoning, which are crucial next steps in computer vision and AI. The first part of the talk will describe our work on understanding preliminary physics from images, and the second part of the talk will be about our recent work on using Reinforcement Learning and Imitation Learning to perform tasks in the challenging AI2-THOR environment.

Speaker Biography

Roozbeh Mottaghi is a Research Scientist at Allen Institute for Artificial Intelligence (AI2). Prior to joining AI2, he was a post-doctoral researcher at the Computer Science Department at Stanford University. He obtained his PhD in Computer Science in 2013 from UCLA. His research is mainly focused on computer vision and machine learning.