MemCat: A new category-based image set quantified on memorability

doi:None

Title	Authors

Home

We present a new category-based set of 10K images quantified on memorability. The set consists of five broader memorability-relevant semantic categories (animal, sports, food, landscapes, vehicles), with 2K exemplars each, further divided into different subcategories (e.g., bear, pigeon, cat, etc. for animal). The images were sourced from existing image sets: ImageNet, COCO, Open Images Dataset, and SUN. Care was taken to avoid major influences of more high-level image aspects (e.g., recognizable places, text). To quantify the set on memorability, we used a repeat-detection memory game on Amazon's Mechanical Turk.

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.

This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.

Create an Account Learn More Hide this message

Main content

Home

Menu

Start managing your projects on the OSF today.

Main content

Links to this project

Home

Menu

Add new wiki page

Page permissions have changed

Wiki page deleted

Connected to the collaborative wiki

Connecting to the collaborative wiki

Collaborative wiki is unavailable

Browser unsupported

Start managing your projects on the OSF today.