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BizGen: Advancing Article-level Visual Text Rendering for Infographics Generation (Glyph-ByT5-v3) (Eval Output)
Dataset Overview
This dataset supports research in article-level visual text rendering for business content generation, including infographics and presentation slides with ultra-dense layouts.
Key Features
π Layout Capabilities
β’ Supports ultra-dense layouts with 50+ layers β’ Handles article-level descriptive prompts (>1000 tokens) β’ Generates high-resolution outputs up to 2240Γ896 pixels
π Multilingual Support
β’ Provides visual text rendering in 10 languages β’ Maintains high spelling accuracy across languages
π¨ Generation Flexibility
β’ Enables layer-wise detail refinement through layout-conditional CFG β’ Supports diverse business content generation (infographics, slides, etc.)
Usage
- Download the dataset from Hugging Face
- Refer to their paper for detailed methodology
- Visit their project page for visual examples
Citation
If you use this dataset in your research, please cite their work:
@article{bizgen2024,
title={BizGen: Advancing Article-level Visual Text Rendering for Infographics Generation},
author={Author List},
journal={arXiv preprint arXiv:2503.20672},
year={2024}
}
License
This dataset is released for academic research purposes only. Commercial use requires separate permission.--- # For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1 # Doc / guide: https://huggingface.co/docs/hub/datasets-cards {}
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