TextBoxes: A Fast Text Detector with a Single Deep Neural Network
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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.
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A Multitask Network for Localization and Recognition of Text in Images
Presents an end-to-end multitask CNN with FPN, dynamic RoI pooling, and convolutional attention for simultaneous lexicon-free text localization and recognition in complex images.
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