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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–225 of 1209 papers

TitleStatusHype
DocLayLLM: An Efficient and Effective Multi-modal Extension of Large Language Models for Text-rich Document UnderstandingCode1
ReadBench: Measuring the Dense Text Visual Reading Ability of Vision-Language ModelsCode1
Rerunning OCR: A Machine Learning Approach to Quality Assessment and Enhancement PredictionCode1
Deep Relational Reasoning Graph Network for Arbitrary Shape Text DetectionCode1
RUArt: A Novel Text-Centered Solution for Text-Based Visual Question AnsweringCode1
Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic LanguagesCode1
DE-GAN: A Conditional Generative Adversarial Network for Document EnhancementCode1
CORU: Comprehensive Post-OCR Parsing and Receipt Understanding DatasetCode1
An Unsupervised method for OCR Post-Correction and Spelling Normalisation for FinnishCode1
SoftCTC -- Semi-Supervised Learning for Text Recognition using Soft Pseudo-LabelsCode1
Stratified Domain Adaptation: A Progressive Self-Training Approach for Scene Text RecognitionCode1
Structured Multimodal Attentions for TextVQACode1
A Deep Learning Approach to Geographical Candidate Selection through Toponym MatchingCode1
Symmetrical Linguistic Feature Distillation with CLIP for Scene Text RecognitionCode1
Data Generation for Post-OCR correction of Cyrillic handwritingCode1
DocLayLLM: An Efficient Multi-modal Extension of Large Language Models for Text-rich Document UnderstandingCode1
End-to-End Information Extraction by Character-Level Embedding and Multi-Stage Attentional U-NetCode1
On Web-based Visual Corpus Construction for Visual Document UnderstandingCode1
Graph Neural Networks and Representation Embedding for Table Extraction in PDF DocumentsCode1
ODM: A Text-Image Further Alignment Pre-training Approach for Scene Text Detection and SpottingCode1
A semi-automatic method for document classification in the shipping industry—0
A second-order orientation-contrast stimulus for population-receptive-field-based retinotopic mapping—0
Amazigh Verb Conjugator—0
A Scalable Handwritten Text Recognition System—0
Artificial neural networks and fuzzy logic for recognizing alphabet characters and mathematical symbols—0
Show:102550
← PrevPage 9 of 49Next →
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