TextBoxes: A Fast Text Detector with a Single Deep Neural Network Article Swipe

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Spotting Computer science Detector Artificial intelligence Text detection Word (group theory) Process (computing) Image (mathematics) Artificial neural network State (computer science) End-to-end principle Keyword spotting Text recognition Pattern recognition (psychology) Speech recognition Natural language processing Algorithm Mathematics Telecommunications Geometry Operating system

Minghui Liao , Baoguang Shi , Xiang Bai , Xinggang Wang , Wenyu Liu ·

YOU? · · 2016 · Open Access · · DOI: https://doi.org/10.48550/arxiv.1611.06779 · OA: W2962773189

This paper presents an end-to-end trainable fast scene text detector, named TextBoxes, which detects scene text with both high accuracy and efficiency in a single network forward pass, involving no post-process except for a standard non-maximum suppression. TextBoxes outperforms competing methods in terms of text localization accuracy and is much faster, taking only 0.09s per image in a fast implementation. Furthermore, combined with a text recognizer, TextBoxes significantly outperforms state-of-the-art approaches on word spotting and end-to-end text recognition tasks.