2021/10/16 by Junlong Li, Li, Junlong, Yiheng Xu +5 · 4 citations
Computer Science · #Handwritten Text Recognition Techniques #Video Analysis and Summarization #Multimodal Machine Learning Applications
paper · pdf · doi:10.48550/arxiv.2110.08518
Multimodal pre-training with text, layout, and image has made significant progress for Visually Rich Document Understanding (VRDU), especially the fixed-layout documents such as scanned document images. While, there are still a large number of digital documents where the layout information is not fixed and needs to be interactively and dynamically rendered for visualization, making existing layout-based pre-training approaches not easy to apply. In this paper, we propose MarkupLM for document understanding tasks with markup languages as the backbone, such as HTML/XML-based documents, where text and markup information is jointly pre-trained. Experiment results show that the pre-trained MarkupLM significantly outperforms the existing strong baseline models on several document understanding tasks. The pre-trained model and code will be publicly available at https://aka.ms/markuplm.