SOTAVerified

Optical Character Recognition (OCR)

Optical Character Recognition or Optical Character Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo, license plates in cars...) or from subtitle text superimposed on an image (for example: from a television broadcast)

Papers

Showing 226250 of 1209 papers

TitleStatusHype
Levenshtein OCRCode0
Arrow-Guided VLM: Enhancing Flowchart Understanding via Arrow Direction EncodingCode0
A Data-driven Investigation of Euphemistic Language: Comparing the usage of "slave" and "servant" in 19th century US newspapersCode0
LEGAL-UQA: A Low-Resource Urdu-English Dataset for Legal Question AnsweringCode0
Are VLMs Really BlindCode0
License Plate Detection and Recognition in Unconstrained ScenariosCode0
Latent Tree Language ModelCode0
LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed BooksCode0
ChemScraper: Leveraging PDF Graphics Instructions for Molecular Diagram ParsingCode0
ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep LearningCode0
KL3M Tokenizers: A Family of Domain-Specific and Character-Level Tokenizers for Legal, Financial, and Preprocessing ApplicationsCode0
KAP: MLLM-assisted OCR Text Enhancement for Hybrid Retrieval in Chinese Non-Narrative DocumentsCode0
Chinese Text in the WildCode0
It Takes Two to Tango: Combining Visual and Textual Information for Detecting Duplicate Video-Based Bug ReportsCode0
Optimal Projections for Discriminative Dictionary Learning using the JL-lemmaCode0
Investigating OCR-Sensitive Neurons to Improve Entity Recognition in Historical DocumentsCode0
Aligned Music Notation and Lyrics TranscriptionCode0
Jochre 3 and the Yiddish OCR corpusCode0
Cleaning Dirty Books: Post-OCR Processing for Previously Scanned TextsCode0
Alleviating Digitization Errors in Named Entity Recognition for Historical DocumentsCode0
Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document ParsingCode0
Adapting the Tesseract Open Source OCR Engine for Multilingual OCRCode0
InstructOCR: Instruction Boosting Scene Text SpottingCode0
Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic ManuscriptsCode0
Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document TranscriptionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DTrOCRAccuracy (%)89.6Unverified
2DTrOCR 105MAccuracy (%)89.6Unverified
3MaskOCR-LAccuracy (%)82.6Unverified
4TransOCRAccuracy (%)72.8Unverified
5SRNAccuracy (%)65Unverified
6MORANAccuracy (%)64.3Unverified
7SEEDAccuracy (%)61.2Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4oAverage Accuracy76.22Unverified
2Gemini-1.5 ProAverage Accuracy76.13Unverified
3Claude-3 SonnetAverage Accuracy67.71Unverified
4RapidOCRAverage Accuracy56.98Unverified
5EasyOCRAverage Accuracy49.3Unverified
#ModelMetricClaimedVerifiedStatus
1STREETSequence error27.54Unverified
2SEESequence error22Unverified
3AttentionOCR_Inception-resnet-v2_LocationSequence error15.8Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-NOPOOLBLEU89.09Unverified
2I2L-STRIPSBLEU89Unverified
#ModelMetricClaimedVerifiedStatus
1TesseractCharacter Error Rate (CER)0.08Unverified
2EasyOCRCharacter Error Rate (CER)0.07Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-STRIPSBLEU88.86Unverified