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 251–275 of 1209 papers

TitleStatusHype
Clustering-based Automatic Construction of Legal Entity Knowledge Base from Contracts—0
ChatSchema: A pipeline of extracting structured information with Large Multimodal Models based on schema—0
Align Me: A framework to generate Parallel Corpus Using OCRs and Bilingual Dictionaries—0
CMUQ@QALB-2014: An SMT-based System for Automatic Arabic Error Correction—0
D\'etection d'erreurs dans des transcriptions OCR de documents historiques par r\'eseaux de neurones r\'ecurrents multi-niveau (Combining character level and word level RNNs for post-OCR error detection)—0
Chart-RCNN: Efficient Line Chart Data Extraction from Camera Images—0
Arabic Character Segmentation Using Projection Based Approach with Profile's Amplitude Filter—0
ChartParser: Automatic Chart Parsing for Print-Impaired—0
ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering—0
A Proposal of Automatic Error Correction in Text—0
A Late Multi-Modal Fusion Model for Detecting Hybrid Spam E-mail—0
ChartEye: A Deep Learning Framework for Chart Information Extraction—0
Chart-based Reasoning: Transferring Capabilities from LLMs to VLMs—0
A preliminary study on similarity-preserving digital book identifiers—0
Chargrid-OCR: End-to-end trainable Optical Character Recognition through Semantic Segmentation and Object Detection—0
Chargrid-OCR: End-to-end Trainable Optical Character Recognition for Printed Documents using Instance Segmentation—0
Applying BLAST to Text Reuse Detection in Finnish Newspapers and Journals, 1771-1910—0
A Black-Box Attack on Optical Character Recognition Systems—0
Detection Masking for Improved OCR on Noisy Documents—0
Directional Global Three-part Image Decomposition—0
Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction—0
A Possibilistic Approach for Automatic Word Sense Disambiguation—0
A Panoramic Survey of Natural Language Processing in the Arab World—0
Challenging America: Modeling language in longer time scales—0
A Language Modelling Approach to Quality Assessment of OCR’ed Historical Text—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