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 101–125 of 1209 papers

TitleStatusHype
Privacy-Aware Document Visual Question AnsweringCode1
DocReal: Robust Document Dewarping of Real-Life Images via Attention-Enhanced Control Point PredictionCode1
Data Generation for Post-OCR correction of Cyrillic handwritingCode1
FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual PromptsCode1
Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth EvaluationCode1
GenKIE: Robust Generative Multimodal Document Key Information ExtractionCode1
DSG: An End-to-End Document Structure GeneratorCode1
Persis: A Persian Font Recognition Pipeline Using Convolutional Neural NetworksCode1
Symmetrical Linguistic Feature Distillation with CLIP for Scene Text RecognitionCode1
UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language ModelCode1
bbOCR: An Open-source Multi-domain OCR Pipeline for Bengali DocumentsCode1
OmniDataComposer: A Unified Data Structure for Multimodal Data Fusion and Infinite Data GenerationCode1
Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character RecognitionCode1
Modular Multimodal Machine Learning for Extraction of Theorems and Proofs in Long Scientific Documents (Extended Version)Code1
UTRNet: High-Resolution Urdu Text Recognition In Printed DocumentsCode1
GenPlot: Increasing the Scale and Diversity of Chart Derendering DataCode1
TransDocAnalyser: A Framework for Offline Semi-structured Handwritten Document Analysis in the Legal DomainCode1
DocFormerv2: Local Features for Document UnderstandingCode1
Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question AnsweringCode1
FuseCap: Leveraging Large Language Models for Enriched Fused Image CaptionsCode1
Super-Resolution of License Plate Images Using Attention Modules and Sub-Pixel Convolution LayersCode1
Exploring Better Text Image Translation with Multimodal CodebookCode1
MRN: Multiplexed Routing Network for Incremental Multilingual Text RecognitionCode1
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented LanguagesCode1
Visual Information Extraction in the Wild: Practical Dataset and End-to-end SolutionCode1
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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