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update dataset overview and ba...
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Feb 10, 2022 9:09 AM
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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},
}
🎉Many thanks to Graviti Open Datasets for contributing the dataset
Basic Information
Application ScenariosNot Available
AnnotationsNot Available
TasksNot Available
LicenseCC BY-NC 4.0
Updated on2022-02-10 09:09:38
Metadata
Data TypeNot Available
Data Volume21,384
Annotation Amount0
File Size0.00B
Copyright Owner
Aston University
Annotator
Unknown