Rethinking the Spatial Route Prior in Vision-and-Language Navigation

Understand

Vision-and-language navigation (VLN) is a trending topic which aims to navigate an intelligent agent to an expected position through natural language instructions.

• This work addresses the task of VLN from a previously-ignored aspect, namely the spatial route prior of the navigation scenes.
• A critically enabling innovation of this work is explicitly considering the spatial route prior under several different VLN settings.
• In a most information-rich case of knowing environment maps and admitting shortest-path prior, we observe that given an origin-destination node pair, the internal route can be uniquely determined.