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SemArt
Image Caption
Classification
Aesthetics
|...
License: CC BY-NC 4.0

Overview

Automatic art analysis has been mostly focused on classifying artworks into different artistic
styles. However, understanding an artistic representation involves more complex processes,
such as identifying the elements in the scene or recognizing author influences. We present
SemArt, a multi-modal dataset for semantic art understanding. SemArt is a collection of fine-art
painting images in which each image is associated to a number of attributes and a textual artistic
comment, such as those that appear in art catalogues or museum collections.

Citation

Please use the following citation when referencing the dataset:

@InProceedings{Garcia2018How,
   author    = {Noa Garcia and George Vogiatzis},
   title     = {How to Read Paintings: Semantic Art Understanding with Multi-Modal Retrieval},
   booktitle = {Proceedings of the European Conference in Computer Vision Workshops},
   year      = {2018},
}

License

CC BY-NC 4.0

Data Summary
Type
Image,
Amount
21.384K
Size
3.1GB
Provided by
Aston University
Aston University is a public research university situated in the city centre of Birmingham, England.
| Amount 21.384K | Size 3.1GB
SemArt
Image Caption Classification
Aesthetics
License: CC BY-NC 4.0

Overview

Automatic art analysis has been mostly focused on classifying artworks into different artistic
styles. However, understanding an artistic representation involves more complex processes,
such as identifying the elements in the scene or recognizing author influences. We present
SemArt, a multi-modal dataset for semantic art understanding. SemArt is a collection of fine-art
painting images in which each image is associated to a number of attributes and a textual artistic
comment, such as those that appear in art catalogues or museum collections.

Citation

Please use the following citation when referencing the dataset:

@InProceedings{Garcia2018How,
   author    = {Noa Garcia and George Vogiatzis},
   title     = {How to Read Paintings: Semantic Art Understanding with Multi-Modal Retrieval},
   booktitle = {Proceedings of the European Conference in Computer Vision Workshops},
   year      = {2018},
}

License

CC BY-NC 4.0

0
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