graviti
产品服务
解决方案
知识库
公开数据集
关于我们
SemArt
2D Classification
Aesthetics
|...
许可协议: 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},
}
数据概要
数据格式
image,
数据量
21.384K
文件大小
3.15GB
发布方
Aston University
Aston University is a public research university situated in the city centre of Birmingham, England.
| 数据量 21.384K | 大小 3.15GB
SemArt
2D Classification
Aesthetics
许可协议: 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},
}
0
立即开始构建AI
graviti
wechat-QR
长按保存识别二维码,关注Graviti公众号

Copyright@Graviti
沪ICP备19019574号
沪公网安备 31011002004865号