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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 781–790 of 1209 papers

Title	Date	Tasks	Status	Hype
Automated data extraction of bar chart raster images	Nov 9, 2020	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified	0
An Unsupervised method for OCR Post-Correction and Spelling Normalisation for Finnish	Nov 6, 2020	Machine TranslationNMT	CodeCode Available	1
Handwriting Classification for the Analysis of Art-Historical Documents	Nov 4, 2020	ClassificationGeneral Classification	CodeCode Available	0
Automated Transcription of Non-Latin Script Periodicals: A Case Study in the Ottoman Turkish Print Archive	Nov 2, 2020	HTROptical Character Recognition (OCR)	—Unverified	0
OCR, Classification & Machine Translation (OCCAM)	Nov 1, 2020	Classificationimage-classification	—Unverified	0
Chunk-based Chinese Spelling Check with Global Optimization	Nov 1, 2020	global-optimizationOptical Character Recognition	—Unverified	0
Alleviating Digitization Errors in Named Entity Recognition for Historical Documents	Nov 1, 2020	named-entity-recognitionNamed Entity Recognition	CodeCode Available	0
RUArt: A Novel Text-Centered Solution for Text-Based Visual Question Answering	Oct 24, 2020	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available	1
Persian Handwritten Digit, Character and Word Recognition Using Deep Learning	Oct 24, 2020	Data AugmentationDeep Learning	—Unverified	0
TLGAN: document Text Localization using Generative Adversarial Nets	Oct 22, 2020	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available	1

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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