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arXiv · 1809.08799

Chargrid: Towards Understanding 2D Documents

Anoop Raveendra Katti·Christian Reisswig·Cordula Guder·Sebastian Brarda·Steffen Bickel·Johannes Höhne·Jean Baptiste Faddoul
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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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Anoop Raveendra Katti, Christian Reisswig, Cordula Guder, Sebastian Brarda, Steffen Bickel, Johannes Höhne, Jean Baptiste Faddoul. 2018-09-24. Chargrid: Towards Understanding 2D Documents. https://arxiv.org/abs/1809.08799

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