Visual Intelligence: Machines and Minds

This lecture explores the interaction between machines and minds in the context of visual intelligence, focusing on the work of James J Gibson and the application of perception in active agents. It covers datasets like Imagenet and UCF101, as well as the use of simulations to bridge the gap between virtual and real-world environments. The lecture delves into the Gibson Environment, a platform for virtualizing real spaces, and discusses the challenges of generalization from simulation to reality. It also addresses the importance of mid-level visual representations in improving generalization and sample complexity for learning visuomotor policies.