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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 476–500 of 1209 papers

TitleStatusHype
From Machine Learning to Machine Reasoning—0
ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering—0
A Proposal of Automatic Error Correction in Text—0
Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation—0
ChartEye: A Deep Learning Framework for Chart Information Extraction—0
ExTTNet: A Deep Learning Algorithm for Extracting Table Texts from Invoice Images—0
Extraction of Line Word Character Segments Directly from Run Length Compressed Printed Text Documents—0
Chart-based Reasoning: Transferring Capabilities from LLMs to VLMs—0
Extracting Weighted Language Lexicons from Wikipedia—0
Extracting structured data from invoices—0
Chargrid-OCR: End-to-end trainable Optical Character Recognition through Semantic Segmentation and Object Detection—0
EKTVQA: Generalized use of External Knowledge to empower Scene Text in Text-VQA—0
Extending TrOCR for Text Localization-Free OCR of Full-Page Scanned Receipt Images—0
Chargrid-OCR: End-to-end Trainable Optical Character Recognition for Printed Documents using Instance Segmentation—0
A preliminary study on similarity-preserving digital book identifiers—0
Applying BLAST to Text Reuse Detection in Finnish Newspapers and Journals, 1771-1910—0
Generating Monolingual Dataset for Low Resource Language Bodo from old books using Google Keep—0
A Late Multi-Modal Fusion Model for Detecting Hybrid Spam E-mail—0
A Black-Box Attack on Optical Character Recognition Systems—0
Extended Named Entities Annotation on OCRed Documents: From Corpus Constitution to Evaluation Campaign—0
Exploring Sparse Spatial Relation in Graph Inference for Text-Based VQA—0
Geometric Rectification of Creased Document Images based on Isometric Mapping—0
Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction—0
A Possibilistic Approach for Automatic Word Sense Disambiguation—0
Exploring AI-based System Design for Pixel-level Protected Health Information Detection in Medical Images—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