mlsanityData to 7 Oct 2026

JSTR: Judgment Improves Scene Text Recognition

arXiv 2404.05967 ↗First posted 9 Apr 2024cs.CV cs.AI cs.CLcited by 1

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Abstract (arXiv)

In this paper, we present a method for enhancing the accuracy of scene text recognition tasks by judging whether the image and text match each other. While previous studies focused on generating the recognition results from input images, our approach also considers the model's misrecognition results to understand its error tendencies, thus improving the text recognition pipeline. This method boosts text recognition accuracy by providing explicit feedback on the data that the model is likely to misrecognize by predicting correct or incorrect between the image and text. The experimental results on publicly available datasets demonstrate that our proposed method outperforms the baseline and state-of-the-art methods in scene text recognition.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 26 of its 37 references that are in the map. First posted on arXiv 9 Apr 2024.

Builds on

26 of 37 references.

References · 26

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14 more
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Citing papers per year: 2024: 1.

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  1. 2024JaPOC: Japanese Post-OCR Correction Benchmark using Voucherscited by 1