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Every Picture Tells a Story: Generating Sentences from Images

  • Ali Farhadi
  • Mohsen Hejrati
  • Mohammad Amin Sadeghi
  • Peter Young
  • Cyrus Rashtchian
  • Julia Hockenmaier
  • David Forsyth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6314)

Abstract

Humans can prepare concise descriptions of pictures, focusing on what they find important. We demonstrate that automatic methods can do so too. We describe a system that can compute a score linking an image to a sentence. This score can be used to attach a descriptive sentence to a given image, or to obtain images that illustrate a given sentence. The score is obtained by comparing an estimate of meaning obtained from the image to one obtained from the sentence. Each estimate of meaning comes from a discriminative procedure that is learned using data. We evaluate on a novel dataset consisting of human-annotated images. While our underlying estimate of meaning is impoverished, it is sufficient to produce very good quantitative results, evaluated with a novel score that can account for synecdoche.

Keywords

Machine Translation Head Noun Node Feature Generate Sentence Edge Potential 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ali Farhadi
    • 1
  • Mohsen Hejrati
    • 2
  • Mohammad Amin Sadeghi
    • 2
  • Peter Young
    • 1
  • Cyrus Rashtchian
    • 1
  • Julia Hockenmaier
    • 1
  • David Forsyth
    • 1
  1. 1.Computer Science DepartmentUniversity of Illinois at Urbana-Champaign 
  2. 2.Computer Vision Group, School of MathematicsInstitute for studies in theoretical Physics and Mathematics(IPM) 

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