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

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Showing 501–525 of 1209 papers

TitleStatusHype
A Possibilistic Approach for Automatic Word Sense Disambiguation—0
Exploring AI-based System Design for Pixel-level Protected Health Information Detection in Medical Images—0
GlyphMastero: A Glyph Encoder for High-Fidelity Scene Text Editing—0
GMN: Generative Multi-modal Network for Practical Document Information Extraction—0
Exploiter des mod\`eles de langue pour \'evaluer des sorties de logiciels d'OCR pour des documents fran du XVIIe si\`ecle ()—0
TextSleuth: Towards Explainable Tampered Text Detection—0
Challenging America: Modeling language in longer time scales—0
A Panoramic Survey of Natural Language Processing in the Arab World—0
Grouping Language Model Boundary Words to Speed K--Best Extraction from Hypergraphs—0
GroupLink: An End-to-end Multitask Method for Word Grouping and Relation Extraction in Form Understanding—0
A Language Modelling Approach to Quality Assessment of OCR’ed Historical Text—0
Explainable Publication Year Prediction of Eighteenth Century Texts with the BERT Model—0
Every Pixel Tells a Story: End-to-End Urdu Newspaper OCR—0
Challenging America: Modeling language in longer time scales—0
Evaluating Usage of Images for App Classification—0
CG-DIQA: No-reference Document Image Quality Assessment Based on Character Gradient—0
Evaluating Inter-Annotator Agreement on Historical Spelling Normalization—0
Evaluating BERT-based Scientific Relation Classifiers for Scholarly Knowledge Graph Construction on Digital Library Collections—0
Estimating Post-OCR Denoising Complexity on Numerical Texts—0
ERPA: Efficient RPA Model Integrating OCR and LLMs for Intelligent Document Processing—0
CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy—0
Adapting Multilingual Embedding Models to Historical Luxembourgish—0
EraseNet: A Recurrent Residual Network for Supervised Document Cleaning—0
Entropy Heat-Mapping: Localizing GPT-Based OCR Errors with Sliding-Window Shannon Analysis—0
Enhancing Vehicle Entrance and Parking Management: Deep Learning Solutions for Efficiency and Security—0
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All datasetsBenchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical StudyVideoDB's OCR Benchmark Public CollectionFSNS - TestI2L-140KSUTim2latex-100k

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DTrOCRAccuracy (%)89.6—Unverified
2DTrOCR 105MAccuracy (%)89.6—Unverified
3MaskOCR-LAccuracy (%)82.6—Unverified
4TransOCRAccuracy (%)72.8—Unverified
5SRNAccuracy (%)65—Unverified
6MORANAccuracy (%)64.3—Unverified
7SEEDAccuracy (%)61.2—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4oAverage Accuracy76.22—Unverified
2Gemini-1.5 ProAverage Accuracy76.13—Unverified
3Claude-3 SonnetAverage Accuracy67.71—Unverified
4RapidOCRAverage Accuracy56.98—Unverified
5EasyOCRAverage Accuracy49.3—Unverified
#ModelMetricClaimedVerifiedStatus
1STREETSequence error27.54—Unverified
2SEESequence error22—Unverified
3AttentionOCR_Inception-resnet-v2_LocationSequence error15.8—Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-NOPOOLBLEU89.09—Unverified
2I2L-STRIPSBLEU89—Unverified
#ModelMetricClaimedVerifiedStatus
1TesseractCharacter Error Rate (CER)0.08—Unverified
2EasyOCRCharacter Error Rate (CER)0.07—Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-STRIPSBLEU88.86—Unverified