Clothing Attributes Dataset
Abstract/Contents
- Abstract
- We introduce the Clothing Attribute Dataset for promoting research in learning visual attributes for objects. The dataset contains 1856 images, with 26 ground truth clothing attributes such as "long-sleeves", "has collar", and "striped pattern". The labels were collected using Amazon Mechanical Turk.
Description
| Type of resource | software, multimedia |
|---|---|
| Date created | 2011 |
Creators/Contributors
| Author | Chen, Huizhong | |
|---|---|---|
| Author | Gallagher, Andrew | |
| Author | Girod, Bernd |
Subjects
| Subject | Computer vision |
|---|---|
| Subject | attribute learning |
| Subject | object recognition |
| Genre | Dataset |
Bibliographic information
| Related Publication | Huizhong Chen, Andrew Gallagher, and Bernd Girod, "Describing Clothing by Semantic Attributes", European Conference on Computer Vision (ECCV), October 2012. http://dx.doi.org/10.1007/978-3-642-33712-3_44 |
|---|---|
| Location | https://purl.stanford.edu/tb980qz1002 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
Preferred citation
- Preferred Citation
- Huizhong Chen, Andrew Gallagher, and Bernd Girod, "Describing Clothing by Semantic Attributes", European Conference on Computer Vision (ECCV), October 2012.
Collection
Research Datasets for Image, Video, and Multimedia Systems Group at Stanford
View other items in this collection in SearchWorksContact information
- Contact
- hchen2@stanford.edu
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