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ICDAR2019 Competition on Scanned Receipt OCR and Information Extraction

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arxiv 2103.10213 v1 pith:Z2MZG3XK submitted 2021-03-18 cs.AI

classification cs.AI
keywords scannedcompetitionreceiptsroietaskextractioninformationreceipts
verification ladder T0 review T1 audit T2 compute T3 formal
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Scanned receipts OCR and key information extraction (SROIE) represent the processeses of recognizing text from scanned receipts and extracting key texts from them and save the extracted tests to structured documents. SROIE plays critical roles for many document analysis applications and holds great commercial potentials, but very little research works and advances have been published in this area. In recognition of the technical challenges, importance and huge commercial potentials of SROIE, we organized the ICDAR 2019 competition on SROIE. In this competition, we set up three tasks, namely, Scanned Receipt Text Localisation (Task 1), Scanned Receipt OCR (Task 2) and Key Information Extraction from Scanned Receipts (Task 3). A new dataset with 1000 whole scanned receipt images and annotations is created for the competition. In this report we will presents the motivation, competition datasets, task definition, evaluation protocol, submission statistics, performance of submitted methods and results analysis.

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  1. FormStruct-Bench:A Hierarchical and Diagnostic Benchmark for Table-Form Document Structure Recognition

    cs.CV 2026-08 unverdicted novelty 6.0 of 10

    FormStruct-Bench is a hierarchical benchmark showing that current table-form recognition systems reach 83.85% at document level but under 18% on fine-grained structural scores.

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