Canonical Correlation Inference for Mapping Abstract Scenes to Text

08/09/2016

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by   Nikos Papasarantopoulos, et al.

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We describe a technique for structured prediction, based on canonical correlation analysis. Our learning algorithm finds two projections for the input and the output spaces that aim at projecting a given input and its correct output into points close to each other. We demonstrate our technique on a language-vision problem, namely the problem of giving a textual description to an "abstract scene".