Semantic Image-Text-Classes

doi:doi:10.25835/0010577

Semantic Image-Text-Classes

This dataset is introduced by the paper "Understanding, Categorizing and Predicting Semantic Image-Text Relations".

If you are using this dataset it in your work, please cite:

@inproceedings{otto2019understanding, title={Understanding, Categorizing and Predicting Semantic Image-Text Relations}, author={Otto, Christian and Springstein, Matthias and Anand, Avishek and Ewerth, Ralph}, booktitle={In Proceedings of ACM International Conference on Multimedia Retrieval (ICMR 2019)}, year={2019} }

To create the full tar use the following command in the command line:

cat train.tar.part* > train_concat.tar

Then simply untar it via

tar -xf train_concat.tar

The jsonl files contain metadata of the following format:

id, origin, CMI, SC, STAT, ITClass, text, tagged text, image_path

License Information:

This dataset is composed of various open access sources as described in the paper. We thank all the original authors for their work.

Pitt Image Ads Dataset: http://people.cs.pitt.edu/~kovashka/ads/
Image-Net challenge: http://image-net.org/
Visual Storytelling Dataset (VIST): http://visionandlanguage.net/VIST/
Wikipedia: https://www.wikipedia.org/
Microsoft COCO: http://cocodataset.org/#home

BibTex:

@dataset{Christian_Otto_and__Matthias_Springstein_and__Avishek_Anand_and__Ralph_Ewerth_2019,
    abstract = {This dataset is introduced by the paper "Understanding, Categorizing and Predicting Semantic Image-Text Relations".

If you are using this dataset it in your work, please cite:

```
@inproceedings{otto2019understanding,
title={Understanding, Categorizing and Predicting Semantic Image-Text Relations},
author={Otto, Christian and Springstein, Matthias and Anand, Avishek and Ewerth, Ralph},
booktitle={In Proceedings of ACM International Conference on Multimedia Retrieval (ICMR 2019)},
year={2019}
}
```

To create the full tar use the following command in the command line:
> cat train.tar.part* > train_concat.tar

Then simply untar it via
> tar -xf train_concat.tar

The jsonl files contain metadata of the following format:

> id, origin, CMI, SC, STAT, ITClass, text, tagged text, image_path

License Information:

This dataset is composed of various open access sources as described in the paper. We thank all the original authors for their work.

* Pitt Image Ads Dataset: http://people.cs.pitt.edu/~kovashka/ads/
* Image-Net challenge: http://image-net.org/
* Visual Storytelling Dataset (VIST): http://visionandlanguage.net/VIST/
* Wikipedia: https://www.wikipedia.org/
* Microsoft COCO:  http://cocodataset.org/#home},
    author = {Christian Otto and  Matthias Springstein and  Avishek Anand and  Ralph Ewerth},
    doi = {10.25835/0010577},
    institution = {TIB},
    keyword = {'image text classes', 'image text relations', 'multimedia retrieval'},
    month = {apr},
    publisher = {LUIS},
    title = {Semantic Image-Text-Classes},
    url = {https://service.tib.eu/ldmservice/vdataset/luh-image-text-classes},
    year = {2019}
}