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 276–300 of 1209 papers

TitleStatusHype
Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document TranscriptionCode0
Brno Mobile OCR DatasetCode0
An Open Source Contractual Language Understanding Application Using Machine LearningCode0
Optimal Projections for Discriminative Dictionary Learning using the JL-lemmaCode0
Advancing Post-OCR Correction: A Comparative Study of Synthetic DataCode0
It Takes Two to Tango: Combining Visual and Textual Information for Detecting Duplicate Video-Based Bug ReportsCode0
Jochre 3 and the Yiddish OCR corpusCode0
LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed BooksCode0
License Plate Detection and Recognition in Unconstrained ScenariosCode0
Mobile User Interface Element Detection Via Adaptively Prompt TuningCode0
Order-preserving Consistency Regularization for Domain Adaptation and GeneralizationCode0
Improving patch-based scene text script identification with ensembles of conjoined networksCode0
Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic ManuscriptsCode0
Improving OCR Accuracy on Early Printed Books using Deep Convolutional NetworksCode0
An OCR system for the Unified Northern AlphabetCode0
Improving OCR Accuracy on Early Printed Books by utilizing Cross Fold Training and VotingCode0
Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document ParsingCode0
Implicit Language Model in LSTM for OCRCode0
A Gaussian Process Upsampling Model for Improvements in Optical Character RecognitionCode0
Binary Document Image Super Resolution for Improved Readability and OCR PerformanceCode0
Improving OCR Accuracy on Early Printed Books by combining Pretraining, Voting, and Active LearningCode0
InstructOCR: Instruction Boosting Scene Text SpottingCode0
An Evaluation of OCR on Egocentric DataCode0
BiblioPage: A Dataset of Scanned Title Pages for Bibliographic Metadata ExtractionCode0
iExam: A Novel Online Exam Monitoring and Analysis System Based on Face Detection and RecognitionCode0
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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
1DTrOCR 105MAccuracy (%)89.6—Unverified
2DTrOCRAccuracy (%)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