We identify the desiderata for a comprehensive benchmark and propose Visually Rich Document Understanding (VRDU). VRDU contains two datasets that represent several challenges: rich schema including diverse data types, complex templates, and diversity of …

2022年11月15日 · VRDU contains two datasets that represent several challenges: rich schema including diverse data types as well as hierarchical entities, complex templates including tables and multi-column layouts, and diversity of different layouts (templates) within a …

在本文中，我们提出 LayoutLM 来联合建模跨扫描文档图像的文本和布局信息之间的交互，这有利于大量真实世界的文档图像理解任务，例如从扫描文档中提取信息。 此外，我们还利用图像特征将单词的视觉信息合并到 LayoutLM 中。 据我们所知，这是第一次在文档级预训练的单个框架中联合学习文本和布局。 它在几个下游任务中取得了最新的最新成果，包括表单理解（从 70.72 到 79.27）、收据理解（从 94.02 到 95.24）和文档图像分类（从 93.07 到 94.42）。 代码和预 …

Understanding visually-rich business documents to extract struc-tured data and automate business workflows has been receiving attention both in academia and industry. Although recent multi-modal language models have achieved impressive results, we find that existing benchmarks do not reflect the complexity of real doc-uments seen in industry.

2023年10月1日 · 富文本文档理解（VRDU, Visually-Rich Document Understanding）的目标是分析多种具有丰富结构和复杂格式的扫描/电子文档。 这可以在广泛的文本相关场景中提供帮助，例如报告/收据理解、文档分类、文档视觉问答等。 由于应用场景多样，VRDU在研究领域和工业应用方面都受到了很多关注。 不同于传统的自然语言理解（NLU, Natural Language Understanding），VRDU不仅需要文本的信息，也需要将文档的结构、视觉信息进行结合来 …

2025年3月10日 · To solve these problems, we propose a unified Knowledge-aware prompt-tuning framework for Visual-rich Document Understanding (KnowVrDU) to enable broad utilization for diverse concrete applications and reduce data requirements.

2024年10月14日 · Recent approaches for visually-rich document understanding (VrDU) uses manually annotated semantic groups, where a semantic group encompasses all semantically relevant but not obviously grouped words. As OCR tools are unable to automatically identify such grouping, we argue that current VrDU approaches are unrealistic.

2023年8月9日 · In “ VRDU: A Benchmark for Visually-rich Document Understanding ”, presented at KDD 2023, we announce the release of the new Visually Rich Document Understanding (VRDU) dataset that aims to bridge this gap and help researchers better track progress on document understanding tasks.

2023年4月11日 · One capability is the Active Brake Assist (ABA), which uses the Video Radar Decision Unit (VRDU) to communicate with the front bumper-mounted radar to provide information about potential hazards to the driver. The VRDU may warn the driver of potential hazards and apply partial or full braking, depending on the data being gathered and analyzed.

2024年10月7日 · I am working with the VRDU dataset, and I am attempting to normalize the bounding boxes for use with LayoutLMv3. In your paper, I see that OCR is used, and bounding box annotations are provided. However, I am having trouble aligning the bounding boxes in the dataset with LayoutLMv3's 0-1000 normalized coordinate system.