A Computer Vision Perspective on Analyzing and Synthesizing Geospatial Data

Abstract

The AI era sustains its foundations from the availability of large datasets. Especially geospatial datasets are very interesting from a computer vision perspective, as they enable us to understand the world we live in. Although many application domains arise from analyzing such big data, analysis itself is not enough for impacting lives. As its counter part, synthesis approaches are recently being developed for mimicking real-world data for completing and creating new worlds. In this paper, we will explore not only example analysis methods developed using large public datasets, but also some generative models to propose realistic and impactful solutions for going beyond observations.