Building a Taxonomy of Attributes for Fine-Grained Scene Understanding

  • Published 2011

Abstract

This paper presents the first effort to discover and exploit a diverse taxonomy of scene attributes. Starting with the fine-grained SUN database, we perform crowd-sourced human studies to find over 100 attributes that discriminate between scene categories. We construct an attributelabeled dataset on top of the SUN database [7]. This “SUN Attribute database” spans more than 700 categories and 14,000 images and has potential for use in high-level scene understanding, attribute-based hierarchy construction, and fine-grained scene recognition.

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Cite this paper

@inproceedings{2011BuildingAT, title={Building a Taxonomy of Attributes for Fine-Grained Scene Understanding}, author={}, year={2011} }