Improving object classification using semantic attributes

@inproceedings{Su2010ImprovingOC,
  title={Improving object classification using semantic attributes},
  author={Yu Su and Moray Allan and Fr{\'e}d{\'e}ric Jurie},
  booktitle={BMVC},
  year={2010}
}
This paper shows how semantic attributes can be used to improve object classification. The semantic attributes used fall into five groups: scene (e.g. ‘road’), colour (e.g. ‘green’), part (e.g. ‘face’), shape (e.g. ‘box’), and material (e.g. ‘wood’). We train a set of classifiers for individual semantic attributes, and use them to make predictions on new images (Figure 1). We can then use the scores from the set of classifiers as a low-dimensional image representation. The object classification… CONTINUE READING
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Learning object representations for visual object class recognition

  • Marcin Marszałek, Cordelia Schmid, Hedi Harzallah, Joost van de Weijer
  • Visual Recognition Challenge workshop,
  • 2007
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