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 751–800 of 1209 papers

TitleStatusHype
Robust Text CAPTCHAs Using Adversarial Examples—0
On-Device Document Classification using multimodal features—0
End-to-End Piece-Wise Unwarping of Document Images—0
Iranis: A Large-scale Dataset of Farsi License Plate CharactersCode1
NOSE Augment: Fast and Effective Data Augmentation Without Searching—0
BROS: A Pre-trained Language Model for Understanding Texts in Document—0
ConvMath: A Convolutional Sequence Network for Mathematical Expression Recognition—0
Named Entity Recognition in the Legal Domain using a Pointer Generator Network—0
Indonesian ID Card Extractor Using Optical Character Recognition and Natural Language Post-Processing—0
FAWA: Fast Adversarial Watermark Attack on Optical Character Recognition (OCR) SystemsCode1
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
TAP: Text-Aware Pre-training for Text-VQA and Text-CaptionCode1
Confidence-aware Non-repetitive Multimodal Transformers for TextCapsCode1
A Two-Step Approach for Automatic OCR Post-CorrectionCode1
Detecting de minimis Code-Switching in Historical German Books—0
Ad Lingua: Text Classification Improves Symbolism Prediction in Image Advertisements—0
Building a Part-of-Speech Tagged Corpus for Drenjongke (Bhutia)Code0
BennettNLP at SemEval-2020 Task 8: Multimodal sentiment classification Using Hybrid Hierarchical Classifier—0
CSECU\_KDE\_MA at SemEval-2020 Task 8: A Neural Attention Model for Memotion Analysis—0
SIS@IIITH at SemEval-2020 Task 8: An Overview of Simple Text Classification Methods for Meme Analysis—0
Intrinsic Decomposition of Document Images In-the-WildCode1
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
OCR Post Correction for Endangered Language TextsCode1
Automated data extraction of bar chart raster images—0
An Unsupervised method for OCR Post-Correction and Spelling Normalisation for FinnishCode1
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
RUArt: A Novel Text-Centered Solution for Text-Based Visual Question AnsweringCode1
Persian Handwritten Digit, Character and Word Recognition Using Deep Learning—0
TLGAN: document Text Localization using Generative Adversarial NetsCode1
Boosting High-Level Vision with Joint Compression Artifacts Reduction and Super-Resolution—0
DE-GAN: A Conditional Generative Adversarial Network for Document EnhancementCode1
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
Tokenization Repair in the Presence of Spelling ErrorsCode1
Table Structure Recognition using Top-Down and Bottom-Up CuesCode1
Finding the Evidence: Localization-aware Answer Prediction for Text Visual Question Answering—0
A Large Multi-Target Dataset of Common Bengali Handwritten GraphemesCode1
Hamming OCR: A Locality Sensitive Hashing Neural Network for Scene Text Recognition—0
Towards Image-based Automatic Meter Reading in Unconstrained Scenarios: A Robust and Efficient Approach—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