Attribute learning in large-scale datasets

Olga Russakovsky, Li Fei-Fei

Research output: Contribution to journalConference articlepeer-review

34 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1-14
Number of pages14
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6553 LNCS
Issue numberPART 1
StatePublished - 2012
Externally publishedYes
Event11th European Conference on Computer Vision, ECCV 2010 - Heraklion, Crete, Greece
Duration: Sep 10 2010Sep 11 2010

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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