Dataset Card for Magazine

Dataset Description

• Homepage: https://xtqiao.com/projects/content_aware_layout/
• Repository: https://github.com/creative-graphic-design/huggingface-datasets/tree/main/datasets/Magazine
• Hugging Face Dataset: https://huggingface.co/datasets/creative-graphic-design/Magazine
• Paper (SIGGRAPH 2019): https://dl.acm.org/doi/10.1145/3306346.3322971

Dataset Summary

Magazine is a magazine layout dataset released with Content-aware Generative Modeling of Graphic Design Layouts. The paper studies graphic layout generation conditioned on visual and textual content and introduces a large-scale magazine layout dataset with fine-grained layout annotations and keyword labels.

Supported Tasks and Leaderboards

The dataset supports content-aware layout generation, graphic layout modeling, and image-conditioned design generation. No public leaderboard is bundled with this Hugging Face packaging.

Languages

The source magazine pages and keywords are primarily English (en).

Dataset Structure

Data Fields

Each row contains filename, category, size, elements, keywords, and images.

Data Splits

Dataset Creation

The original release includes magazine images and fine-grained layout annotations for content-aware layout modeling.

Considerations for Using the Data

The dataset represents magazine layouts from the upstream collection and may not cover all editorial styles, languages, or publication domains.

Additional Information

Licensing Information

The dataset license is not specified in the local loader metadata. Users should verify the upstream terms before redistribution or commercial use.

Citation Information

@article{zheng2019content,
  title={Content-aware generative modeling of graphic design layouts},
  author={Zheng, Xinru and Qiao, Xiaotian and Cao, Ying and Lau, Rynson W. H.},
  journal={ACM Transactions on Graphics},
  volume={38},
  number={4},
  year={2019}
}

Contributions

Thanks to the authors of the original Magazine layout dataset.