TOUCHDOWN: Natural Language Navigation and Spatial Reasoning in Visual Street Environments.

Howard Chen, Alane Suhr, Dipendra Misra, Noah Snavely, Yoav Artzi

Abstract: We study the problem of jointly reasoning about language and vision through a navigation and spatial reasoning task. We introduce the Touchdown task and dataset, where an agent must first follow navigation instructions in a Street View environment to a goal position, and then guess a location in its observed environment described in natural language to find a hidden object. The data contains 9326 examples of English instructions and spatial descriptions paired with demonstrations. We perform qualitative linguistic analysis, and show that the data displays a rich use of spatial reasoning. Empirical analysis shows the data presents an open challenge to existing methods.