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Download the Object Attributes

Annotations of object attributes are freely available for download ( no signing-in required ). The attributes are annotated and verified through Amazon Mechanical Turk.

Currently, we have 25 attributes for ~400 popular synsets available. Please click here to obtain the list of synsets available. For each synset, there are 25 images annotated with the following attributes:

  • Color: black, blue, brown, gray, green, orange, pink, red, violet, white, yellow
  • Pattern: spotted, striped
  • Shape: long, round, rectangular, square
  • Texture: furry, smooth, rough, shiny, metallic, vegetation, wooden, wet

For example:

Labeling procedure (for each image and each attribute):

  • Rather than labeling the entire image, we use the previously collected bounding box annotations to focus on just one part of the image which contains the object of interest.
  • We ask 3-4 workers to provide a binary label indicating whether the object contains the attribute or not.
  • If there is consensus among the workers, we assign the corresponding positive or negative label.
  • Otherwise, we label the attribute as ambiguous for this image.

This data was initially collected for

  • O. Russakovsky and L. Fei-Fei, Attribute Learning in Large-scale Datasets. Proceedings of the 12th European Conference of Computer Vision (ECCV), 1st International Workshop on Parts and Attributes. 2010.
    pdf | bibtex | slides | numerical results
How to download the attributes?
  • We have not yet released the attributes for all synsets. To check the list of synsets with attributes, please use the API: You can click here to obtain the synset names.
  • You can download all the attributes available packaged in one file here. The API will return a Matlab (.mat) file. In the Matlab file, there will be a struct attrann which contains
    • A list of images,
    • A list of bounding boxes (bboxes), one per image. corresponding to the labeled objects. Each bounding boxes contains the fields x1, x2, y1, y2, all normalized to be between 0 and 1,
    • A list of attributes,
    • A matrix of labels of size (number of images) x (number of attributes). A label of 1 (or -1) indicates the presence (or absence) of the attribute, and a label of 0 indicates lack of consensus among the workers.
    Please refer to the README (corrected 1/24/15) for more details about data collection. You also can download the extracted features here. Please refer to the paper for details about feature extraction.
  • When you browse each individual synset ( e.g. Kit fox ), you can download the attributes if there is an icon "Download Attributes" below the image view panel. You can also use the following API to download the attributes of a particular synset:
    The returned Matlab (.mat) file is in the format described above.
To learn more about download using HTTP protocol, please refer to API documentation.