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

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...

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Bibliographic Details
Published in:Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 12530 - 12539
Main Authors: Chen, Howard, Suhr, Alane, Misra, Dipendra, Snavely, Noah, Artzi, Yoav
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2019
Subjects:
Cognition
Data collection
Datasets and Evaluation
Linguistics
Navigation
Spatial databases
Urban areas
Vision + Language
Visual Reasoning
Visualization
ISSN:1063-6919
Online Access:Get full text
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Summary: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.
ISSN:1063-6919
DOI:10.1109/CVPR.2019.01282