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In this paper, we propose an innovative end-to-end subtitle detection andrecognition system for videos in East Asian languages. Our end-to-end systemconsists of multiple stages. Subtitles are firstly detected by a novel imageoperator based on the sequence information of consecutive video frames. Then,an ensemble of Convolutional Neural Networks (CNNs) trained on synthetic datais adopted for detecting and recognizing East Asian characters. Finally, adynamic programming approach leveraging language models is applied toconstitute results of the entire body of text lines. The proposed systemachieves average end-to-end accuracies of 98.2% and 98.3% on 40 videos inSimplified Chinese and 40 videos in Traditional Chinese respectively, which isa significant outperformance of other existing methods. The near-perfectaccuracy of our system dramatically narrows the gap between human cognitiveability and state-of-the-art algorithms used for such a task.

End-to-End Subtitle Detection and Recognition for Videos in East Asian Languages via CNN Ensemble with Near-Human-Level Performance