SUN attribute database: Discovering, annotating, and recognizing scene attributes

In this paper we present the first large-scale scene attribute database. First, we perform crowd-sourced human studies to find a taxonomy of 102 discriminative attributes. Next, we build the "SUN attribute database" on top of the diverse SUN categorical database. Our attribute database spa...

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Bibliographic Details
Published in:2012 IEEE Conference on Computer Vision and Pattern Recognition pp. 2751 - 2758
Main Authors: Patterson, G., Hays, J.
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2012
Subjects:
Accuracy
Humans
Sun
Taxonomy
Training
Visualization
ISBN:9781467312264, 1467312266
ISSN:1063-6919, 1063-6919
Online Access:Get full text
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Summary:In this paper we present the first large-scale scene attribute database. First, we perform crowd-sourced human studies to find a taxonomy of 102 discriminative attributes. Next, we build the "SUN attribute database" on top of the diverse SUN categorical database. Our attribute database spans more than 700 categories and 14,000 images and has potential for use in high-level scene understanding and fine-grained scene recognition. We use our dataset to train attribute classifiers and evaluate how well these relatively simple classifiers can recognize a variety of attributes related to materials, surface properties, lighting, functions and affordances, and spatial envelope properties.
ISBN:9781467312264
1467312266
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2012.6247998