E2E-MLT - an Unconstrained End-to-End Method for Multi-Language Scene Text

An end-to-end method for multi-language scene text localization, recognition and script identification is proposed. The approach is based on a set of convolutional neural nets. The method, called E2E-MLT, achieves state-of-the-art performance for both joint localization and script identification in natural images and in cropped word script identification. E2E-MLT is the first published multi-language OCR for scene text. The experiments show that obtaining accurate multi-language multi-script annotations is a challenging problem.