Embodied perception in-the-wild
Computer vision is undergoing a period of rapid progress, rekindling the relationship between perception, action, and cognition. Such connections may be best practically explored in the context of autonomous robotics. In this talk, I will discuss perceptual understanding tasks motivated by embodied robots "in-the-wild", focusing on the illustrative case of autonomous vehicles. I will argue that many challenges that surface are not well-explored in contemporary computer vision. These include streaming computation with bounded resources, generalization via spatiotemporal grouping, online behavioral forecasting, and self-aware processing that can recognize anomalous out-of-sample data. I will conclude with a description of open challenges for embodied perception in-the-wild.