introduce a web image dataset created by Lab for Media Search
in National University of Singapore. The
dataset includes: (1) 269,648 images and the associated tags from Flickr, with a
total number of 5,018 unique tags; (2) six types of low-level features extracted
from these images, including 64-D color histogram, 144-D color correlogram, 73-D
edge direction histogram, 128-D wavelet texture, 225-D block-wise color moments and 500-D bag of words based
on SIFT descriptions; and (3) ground-truth for 81 concepts that can be used for
evaluation. Based on this dataset, we identify several research issues on web
image annotation and retrieval. We also provide the baseline results for web
image annotation by learning from the tags using the traditional k-NN
algorithm. The benchmark results show that it is possible to learn models from
these data to help general image retrieval.
Tat-Seng Chua, Jinhui
Tang, Richang Hong, Haojie Li, Zhiping Luo, and Yan-Tao Zheng. "NUS-WIDE: A Real-World Web Image
Database from National University of Singapore",
ACM International Conference on Image and Video Retrieval.
Greece. Jul. 8-10, 2009.
For any questions regarding NUS-WIDE dataset, please contact Mr. Shang Xindi (shangxin AT comp.nus.edu.sg).
facilitate your research, we have uploaded the URLs of all the images except
those that have been removed or are inaccessible now.
exif and geo-info for the images from a fraction of the dataset are available
more detailed descriptions of the dataset, see
(1.1 GB file)
(25 MB file)
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We provide a light version of NUS-WIDE
dataset, named NUS-WIDE-LITE along with one object image dataset, named
NUS-WIDE-OBJECT and one scene image dataset, named NUS-WIDE-SCENE. The image
dataset can be obtained via sending a request email to us. Specifically, the
researchers interested in the dataset should download and fill up the
Agreement and Disclaimer
Form and send it back to us. We will then email you
the instructions to download the dataset at our discretion.
(110 MB file)
(62 MB file)
(70 MB file)