Paper

Chargrid-OCR: End-to-end Trainable Optical Character Recognition for Printed Documents using Instance Segmentation

We present an end-to-end trainable approach for Optical Character Recognition (OCR) on printed documents. Specifically, we propose a model that predicts a) a two-dimensional character grid (\emph{chargrid}) representation of a document image as a semantic segmentation task and b) character boxes for delineating character instances as an object detection task... (read more)

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