تقرير
DocParser: End-to-end OCR-free Information Extraction from Visually Rich Documents
| العنوان: | DocParser: End-to-end OCR-free Information Extraction from Visually Rich Documents |
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| المؤلفون: | Dhouib, Mohamed, Bettaieb, Ghassen, Shabou, Aymen |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence |
| الوصف: | Information Extraction from visually rich documents is a challenging task that has gained a lot of attention in recent years due to its importance in several document-control based applications and its widespread commercial value. The majority of the research work conducted on this topic to date follow a two-step pipeline. First, they read the text using an off-the-shelf Optical Character Recognition (OCR) engine, then, they extract the fields of interest from the obtained text. The main drawback of these approaches is their dependence on an external OCR system, which can negatively impact both performance and computational speed. Recent OCR-free methods were proposed to address the previous issues. Inspired by their promising results, we propose in this paper an OCR-free end-to-end information extraction model named DocParser. It differs from prior end-to-end approaches by its ability to better extract discriminative character features. DocParser achieves state-of-the-art results on various datasets, while still being faster than previous works. Comment: The 17th International Conference on Document Analysis and Recognition |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2304.12484 |
| رقم الأكسشن: | edsarx.2304.12484 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |