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Attribute Learning in Large-Scale Datasets

  • Olga Russakovsky
  • Li Fei-Fei
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6553)

Abstract

We consider the task of learning visual connections between object categories using the ImageNet dataset, which is a large-scale dataset ontology containing more than 15 thousand object classes. We want to discover visual relationships between the classes that are currently missing (such as similar colors or shapes or textures). In this work we learn 20 visual attributes and use them in a zero-shot transfer learning experiment as well as to make visual connections between semantically unrelated object categories.

Keywords

Object Class Object Category Striped Zebra Attribute Learn Semantic Hierarchy 
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 2012

Authors and Affiliations

  • Olga Russakovsky
    • 1
  • Li Fei-Fei
    • 1
  1. 1.Stanford UniversityUSA

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