论文标题
Docbank：用于文档布局分析的基准数据集
DocBank: A Benchmark Dataset for Document Layout Analysis
论文作者
论文摘要
文档布局分析通常依靠计算机视觉模型来理解文档，同时忽略对于捕获至关重要的文本信息。同时，具有视觉和文本信息的高质量标签数据集仍然不足。在本文中，我们提出\ textbf {docbank}，这是一个基准数据集，其中包含500k文档页面，其中包含具有细粒的令牌级注释，用于文档布局分析。 Docbank是使用一种简单但有效的方式构建的，从\ latex {}文档中可用的弱监督下进行构建。使用Docbank，可以公平地比较来自不同模式的模型，将进一步研究多模式的方法并提高文档布局分析的性能。我们建造了几个强大的基线，并手动拆分火车/开发/测试集进行评估。实验结果表明，在Docbank培训的模型可以准确识别各种文档的布局信息。 Docbank数据集可在\ url {https://github.com/doc-analysis/docbank}上公开获得。
Document layout analysis usually relies on computer vision models to understand documents while ignoring textual information that is vital to capture. Meanwhile, high quality labeled datasets with both visual and textual information are still insufficient. In this paper, we present \textbf{DocBank}, a benchmark dataset that contains 500K document pages with fine-grained token-level annotations for document layout analysis. DocBank is constructed using a simple yet effective way with weak supervision from the \LaTeX{} documents available on the arXiv.com. With DocBank, models from different modalities can be compared fairly and multi-modal approaches will be further investigated and boost the performance of document layout analysis. We build several strong baselines and manually split train/dev/test sets for evaluation. Experiment results show that models trained on DocBank accurately recognize the layout information for a variety of documents. The DocBank dataset is publicly available at \url{https://github.com/doc-analysis/DocBank}.
