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 751–775 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
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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