Caltech-UCSD Birds 200
Caltech-UCSD Birds 200 (CUB-200) is a challenging image dataset annotated with 200 bird species (mostly North American).. It was created to enable the study of subordinate categorization, which is not possible with other popular datasets that focus on basic level categories (such as PASCAL VOC, Caltech-101, etc). The images were downloaded from the website Flickr and filtered by workers on Amazon Mechanical Turk. Each image is annotated with a bounding box, a rough bird segmentation, and a set of attribute labels.
- Number of categories: 200
- Number of images: 11,788
- Annotations per image: 15 Part Locations, 312 Binary Attributes, 1 Bounding Box
For detailed information about the dataset, please see the technical report and the dataset link.
Caltech (CNS-TR-201), 2010.