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Chargrid: Towards Understanding 2D Documents

2018/09/24 by Anoop R Katti, Katti, Anoop Raveendra, Christian Reisswig +11 · 7 citations
Computer Science · #Handwritten Text Recognition Techniques #Natural Language Processing Techniques #Music and Audio Processing

paper · pdf · doi:10.48550/arxiv.1809.08799

Abstract

We introduce a novel type of text representation that preserves the 2D layout of a document. This is achieved by encoding each document page as a two-dimensional grid of characters. Based on this representation, we present a generic document understanding pipeline for structured documents. This pipeline makes use of a fully convolutional encoder-decoder network that predicts a segmentation mask and bounding boxes. We demonstrate its capabilities on an information extraction task from invoices and show that it significantly outperforms approaches based on sequential text or document images.

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