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 101125 of 1209 papers

TitleStatusHype
Efficient OCR for Building a Diverse Digital HistoryCode1
German Parliamentary Corpus (GerParCor)Code1
Exploring Cross-Image Pixel Contrast for Semantic SegmentationCode1
An Unsupervised method for OCR Post-Correction and Spelling Normalisation for FinnishCode1
A Two-Step Approach for Automatic OCR Post-CorrectionCode1
DSG: An End-to-End Document Structure GeneratorCode1
Document Dewarping with Control PointsCode1
hmBERT: Historical Multilingual Language Models for Named Entity RecognitionCode1
DocTr: Document Image Transformer for Geometric Unwarping and Illumination CorrectionCode1
EAST: An Efficient and Accurate Scene Text DetectorCode1
An Empirical Study of Scaling Law for OCRCode1
Intrinsic Decomposition of Document Images In-the-WildCode1
DocReal: Robust Document Dewarping of Real-Life Images via Attention-Enhanced Control Point PredictionCode1
LAMBERT: Layout-Aware (Language) Modeling for information extractionCode1
A Benchmark and Dataset for Post-OCR text correction in SanskritCode1
DocLayLLM: An Efficient Multi-modal Extension of Large Language Models for Text-rich Document UnderstandingCode1
DocParser: End-to-end OCR-free Information Extraction from Visually Rich DocumentsCode1
ARB: A Comprehensive Arabic Multimodal Reasoning BenchmarkCode1
DocScanner: Robust Document Image Rectification with Progressive LearningCode1
Easter2.0: Improving convolutional models for handwritten text recognitionCode1
From Text to Pixel: Advancing Long-Context Understanding in MLLMsCode1
LogicOCR: Do Your Large Multimodal Models Excel at Logical Reasoning on Text-Rich Images?Code1
Digitizing Historical Balance Sheet Data: A Practitioner's GuideCode1
Detection of Furigana Text in ImagesCode1
DiT: Self-supervised Pre-training for Document Image TransformerCode1
Show:102550
← PrevPage 5 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DTrOCR 105MAccuracy (%)89.6Unverified
2DTrOCRAccuracy (%)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