Animals

The original version of the following list of visual stimulus sets was compiled by Johanna Margret Sigurdardottir and will be updated as needed. We neither host nor do we provide copies of the stimuli. Researchers who may wish to use a particular stimulus set should seek further information, including on possible licences, e.g. by following the provided web links, reading the referenced papers, and/or emailing the listed contact person/persons for a particular stimulus set. If you notice an error, know of a stimulus set that should be included, or have any other questions or comments, please contact Heida Maria Sigurdardottir (heidasi(Replace this parenthesis with the @ sign)hi.is). The list is provided as is without any warranty whatsoever.

These data sets contain various pictures of animals.

Animacy x Size

Description

The set contains 120 pictures of animals. Each animal is shown isolated with a white background and not part of a scene. The pictures are split into two categories: small animals and large animals. Additionally, the set contains 120 images of objects. Each object is shown isolated with a white background. 60 of these objects are considered small in real-life and 60 are considered large.

Link

http://konklab.fas.harvard.edu/#

License
The dataset is available to download as a ZIP file here.

Reference(s)

Caramazza, A., Konkle, T. (2013). Tripartite Organization of the Ventral Stream by Animacy and Object Size. The Journal of Neuroscience, 33(25), 10235-10242.

Animals with Attributes 2

Description

This dataawr contains 37.322 images of 50 animal classes with pre-extracted feature representations for each image, intended as a bencmarch for transfer-learning algorithms. The image data was collected from public sources, such as Flickr, in 2016. It only includes images that are licensed for free use and redistribution.

Link

https://cvml.ist.ac.at/AwA2/

License

The database is available for download at the above link under the heading ‘Downloads’.

Reference(s)

Xian, Y., Lampert, C. H., Schiele, B., & Akata, Z. (2018). Zero-shot learning—a comprehensive evaluation of the good, the bad and the ugly. IEEE transactions on pattern analysis and machine intelligence41(9), 2251-2265.

Caltech-UCSD Birds-200-2011

Description

This database has 11.788 pictures of birds from 200 species. All the birds are part of a scene.

Link

http://www.vision.caltech.edu/visipedia/CUB-200-2011.html

License

The dataset is available for download under the ‘Download’ section of the above website.

Reference(s)

Wah, C., Branson, S., Welinder, P., Perona, P., & Belongie, S. (2011). The caltech-ucsd birds-200-2011 dataset.

KTH-Animals

Description

This database has images of 19 living animal species outdoors. The images have been divided into foreground and background regions.  There are about 62 to over 100 images of each species.

Link

http://www.csc.kth.se/~heydarma/Datasets.html

License

The dataset is available for download via the link above.

Reference(s)

Afkham, H. M., Targhi, A. T., Eklundh, J. O., & Pronobis, A. (2008). Joint visual vocabulary for animal classification. In 2008 19th International Conference on Pattern Recognition (pp. 1-4). IEEE.