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 951–960 of 1209 papers

Title	Date	Tasks	Status
An OCR system for the Unified Northern Alphabet	Jan 1, 2019	Optical Character Recognition (OCR)	CodeCode Available
TextNet: Irregular Text Reading from Images with an End-to-End Trainable Network	Dec 24, 2018	Optical Character Recognition (OCR)Text Detection	—Unverified
Dynamic Programming Approach to Template-based OCR	Dec 19, 2018	Optical Character Recognition (OCR)Position	—Unverified
Pay Voice: Point of Sale Recognition for Visually Impaired People	Dec 14, 2018	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Deep Reader: Information extraction from Document images via relation extraction and Natural Language	Dec 11, 2018	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Neural Probabilistic System for Text Recognition	Dec 10, 2018	Optical Character Recognition (OCR)	—Unverified
Binary Document Image Super Resolution for Improved Readability and OCR Performance	Dec 6, 2018	Image Super-ResolutionInformation Retrieval	CodeCode Available
Extracting structured data from invoices	Dec 1, 2018	BIG-bench Machine LearningOptical Character Recognition (OCR)	—Unverified
A Compositional Textual Model for Recognition of Imperfect Word Images	Nov 27, 2018	Optical Character Recognition (OCR)Printed Text Recognition	—Unverified
From Videos to URLs: A Multi-Browser Guide To Extract User's Behavior with Optical Character Recognition	Nov 15, 2018	MarketingOptical Character Recognition	CodeCode Available

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All datasets Benchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical Study VideoDB's OCR Benchmark Public Collection FSNS - Test I2L-140K SUT im2latex-100k

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DTrOCR	Accuracy (%)	89.6	—	Unverified
2	DTrOCR 105M	Accuracy (%)	89.6	—	Unverified
3	MaskOCR-L	Accuracy (%)	82.6	—	Unverified
4	TransOCR	Accuracy (%)	72.8	—	Unverified
5	SRN	Accuracy (%)	65	—	Unverified
6	MORAN	Accuracy (%)	64.3	—	Unverified
7	SEED	Accuracy (%)	61.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GPT-4o	Average Accuracy	76.22	—	Unverified
2	Gemini-1.5 Pro	Average Accuracy	76.13	—	Unverified
3	Claude-3 Sonnet	Average Accuracy	67.71	—	Unverified
4	RapidOCR	Average Accuracy	56.98	—	Unverified
5	EasyOCR	Average Accuracy	49.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STREET	Sequence error	27.54	—	Unverified
2	SEE	Sequence error	22	—	Unverified
3	AttentionOCR_Inception-resnet-v2_Location	Sequence error	15.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	I2L-NOPOOL	BLEU	89.09	—	Unverified
2	I2L-STRIPS	BLEU	89	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Tesseract	Character Error Rate (CER)	0.08	—	Unverified
2	EasyOCR	Character Error Rate (CER)	0.07	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	I2L-STRIPS	BLEU	88.86	—	Unverified