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Computer Science > Computer Vision and Pattern Recognition

arXiv:1506.03500 (cs)
[Submitted on 10 Jun 2015 (v1), last revised 23 Nov 2015 (this version, v2)]

Title:Unveiling the Dreams of Word Embeddings: Towards Language-Driven Image Generation

Authors:Angeliki Lazaridou, Dat Tien Nguyen, Raffaella Bernardi, Marco Baroni
View a PDF of the paper titled Unveiling the Dreams of Word Embeddings: Towards Language-Driven Image Generation, by Angeliki Lazaridou and 3 other authors
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Abstract:We introduce language-driven image generation, the task of generating an image visualizing the semantic contents of a word embedding, e.g., given the word embedding of grasshopper, we generate a natural image of a grasshopper. We implement a simple method based on two mapping functions. The first takes as input a word embedding (as produced, e.g., by the word2vec toolkit) and maps it onto a high-level visual space (e.g., the space defined by one of the top layers of a Convolutional Neural Network). The second function maps this abstract visual representation to pixel space, in order to generate the target image. Several user studies suggest that the current system produces images that capture general visual properties of the concepts encoded in the word embedding, such as color or typical environment, and are sufficient to discriminate between general categories of objects.
Comments: A 6-page version to appear at the Multimodal Machine Learning NIPS 2015 Workshop
Subjects: Computer Vision and Pattern Recognition (cs.CV); Computation and Language (cs.CL)
Cite as: arXiv:1506.03500 [cs.CV]
  (or arXiv:1506.03500v2 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.1506.03500
arXiv-issued DOI via DataCite

Submission history

From: Angeliki Lazaridou [view email]
[v1] Wed, 10 Jun 2015 22:57:20 UTC (2,248 KB)
[v2] Mon, 23 Nov 2015 16:36:48 UTC (2,248 KB)
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Angeliki Lazaridou
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Marco Baroni
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