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 801–825 of 1209 papers

TitleStatusHype
Discovering Airline-Specific Business Intelligence from Online Passenger Reviews: An Unsupervised Text Analytics Approach—0
Vartani Spellcheck -- Automatic Context-Sensitive Spelling Correction of OCR-generated Hindi Text Using BERT and Levenshtein Distance—0
Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps—0
BennettNLP at SemEval-2020 Task 8: Multimodal sentiment classification Using Hybrid Hierarchical Classifier—0
Detecting de minimis Code-Switching in Historical German Books—0
SIS@IIITH at SemEval-2020 Task 8: An Overview of Simple Text Classification Methods for Meme Analysis—0
Ad Lingua: Text Classification Improves Symbolism Prediction in Image Advertisements—0
Building a Part-of-Speech Tagged Corpus for Drenjongke (Bhutia)Code0
CSECU\_KDE\_MA at SemEval-2020 Task 8: A Neural Attention Model for Memotion Analysis—0
A Survey of Deep Learning Approaches for OCR and Document UnderstandingCode0
A Panoramic Survey of Natural Language Processing in the Arab World—0
SuperOCR: A Conversion from Optical Character Recognition to Image Captioning—0
On-Device Text Image Super Resolution—0
Clustering-based Automatic Construction of Legal Entity Knowledge Base from Contracts—0
On-Device Language Identification of Text in Images using Diacritic Characters—0
Automated data extraction of bar chart raster images—0
Handwriting Classification for the Analysis of Art-Historical DocumentsCode0
Automated Transcription of Non-Latin Script Periodicals: A Case Study in the Ottoman Turkish Print Archive—0
OCR, Classification & Machine Translation (OCCAM)—0
Chunk-based Chinese Spelling Check with Global Optimization—0
Alleviating Digitization Errors in Named Entity Recognition for Historical DocumentsCode0
Persian Handwritten Digit, Character and Word Recognition Using Deep Learning—0
Boosting High-Level Vision with Joint Compression Artifacts Reduction and Super-Resolution—0
A Conglomerate of Multiple OCR Table Detection and Extraction—0
DocStruct: A Multimodal Method to Extract Hierarchy Structure in Document for General Form Understanding—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