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Voxel-informed Language Grounding

2022-05-19 17:24:04
Rodolfo Corona, Shizhan Zhu, Dan Klein, Trevor Darrell
arXiv_AI
     
Abstract

Natural language applied to natural 2D images describes a fundamentally 3D world. We present the Voxel-informed Language Grounder (VLG), a language grounding model that leverages 3D geometric information in the form of voxel maps derived from the visual input using a volumetric reconstruction model. We show that VLG significantly improves grounding accuracy on SNARE, an object reference game task. At the time of writing, VLG holds the top place on the SNARE leaderboard, achieving SOTA results with a 2.0% absolute improvement.

Abstract (translated)

URL

https://arxiv.org/abs/2205.09710

PDF

https://arxiv.org/pdf/2205.09710.pdf

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