A Joint Model of Language and Perception for Grounded Attribute Learning A Joint Model of Language and Perception for Grounded Attribute Learning
Paper summary * Task of extracting representations of language tied to physical world * New grounded concepts from a set of scenes containing only sentences, images, and indications of what objects being referred to * System includes: * *Semantic parsing model* * Defines distribution over logical meaning representations for each given sentence * Set of visual attribute classifiers for each possible object in scene * Joint model learning mapping from logical constants in logical form to set of visual attribute classifiers * Extracted depth and RGB values from images as features (shape and color attributes)
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A Joint Model of Language and Perception for Grounded Attribute Learning
Cynthia Matuszek and Nicholas FitzGerald and Luke Zettlemoyer and Liefeng Bo and Dieter Fox
arXiv e-Print archive - 2012 via Local arXiv
Keywords: cs.CL, cs.LG, cs.RO

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Summary by Mihail Eric 9 months ago
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