A context-aware text recognition pipeline that groups and orders words in images and then applies a sequence-to-sequence correction model achieves 90% word accuracy on catalog images and 71% on protest sign images, beating a single-word baseline by roughly five points.
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Deep Neural Network for Semantic-based Text Recognition in Images
A context-aware text recognition pipeline that groups and orders words in images and then applies a sequence-to-sequence correction model achieves 90% word accuracy on catalog images and 71% on protest sign images, beating a single-word baseline by roughly five points.