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 1081–1090 of 1209 papers

Title	Date	Tasks	Status
Finding Names in Trove: Named Entity Recognition for Australian Historical Newspapers	Dec 1, 2015	Clusteringnamed-entity-recognition	—Unverified
Finding the Evidence: Localization-aware Answer Prediction for Text Visual Question Answering	Oct 6, 2020	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Finite State Approach to the Kazakh Nominal Paradigm	Jul 1, 2013	Morphological AnalysisOptical Character Recognition (OCR)	—Unverified
FLELex: a graded lexical resource for French foreign learners	May 1, 2014	Language AcquisitionOptical Character Recognition (OCR)	—Unverified
Font Identification in Historical Documents Using Active Learning	Jan 27, 2016	Active LearningDiversity	—Unverified
Fooling OCR Systems with Adversarial Text Images	Feb 15, 2018	Adversarial TextOptical Character Recognition	—Unverified
FormGym: Doing Paperwork with Agents	Jun 17, 2025	FormInformation Retrieval	—Unverified
Fraunhofer SIT at CheckThat! 2023: Mixing Single-Modal Classifiers to Estimate the Check-Worthiness of Multi-Modal Tweets	Jul 2, 2023	Fact CheckingOptical Character Recognition (OCR)	—Unverified
French Word Recognition through a Quick Survey on Recurrent Neural Networks Using Long-Short Term Memory RNN-LSTM	Apr 10, 2018	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
From Machine Learning to Machine Reasoning	Feb 9, 2011	BIG-bench Machine LearningLanguage Modeling	—Unverified

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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