LabelMe: A Database and Web-Based Tool for Image Annotation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2008-05

AUTHORS

Bryan C. Russell, Antonio Torralba, Kevin P. Murphy, William T. Freeman

ABSTRACT

We seek to build a large collection of images with ground truth labels to be used for object detection and recognition research. Such data is useful for supervised learning and quantitative evaluation. To achieve this, we developed a web-based tool that allows easy image annotation and instant sharing of such annotations. Using this annotation tool, we have collected a large dataset that spans many object categories, often containing multiple instances over a wide variety of images. We quantify the contents of the dataset and compare against existing state of the art datasets used for object recognition and detection. Also, we show how to extend the dataset to automatically enhance object labels with WordNet, discover object parts, recover a depth ordering of objects in a scene, and increase the number of labels using minimal user supervision and images from the web. More... »

PAGES

157-173

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11263-007-0090-8

DOI

http://dx.doi.org/10.1007/s11263-007-0090-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1027534025


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