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 1001–1010 of 1209 papers

Title	Date	Tasks	Status
A Multi-faceted OCR Framework for Artificial Urdu News Ticker Text Recognition	Apr 24, 2018	Optical Character Recognition (OCR)Retrieval	—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
The Monge-Kantorovich Optimal Transport Distance for Image Comparison	Apr 8, 2018	BIG-bench Machine LearningOptical Character Recognition	—Unverified
Neural Monkey: The Current State and Beyond	Mar 1, 2018	Image CaptioningMachine Translation	—Unverified
Chinese Text in the Wild	Feb 28, 2018	Optical Character Recognition (OCR)	CodeCode Available
Improving OCR Accuracy on Early Printed Books using Deep Convolutional Networks	Feb 27, 2018	Optical Character Recognition (OCR)	CodeCode Available
Improving OCR Accuracy on Early Printed Books by combining Pretraining, Voting, and Active Learning	Feb 27, 2018	Active LearningOptical Character Recognition (OCR)	CodeCode Available
Fooling OCR Systems with Adversarial Text Images	Feb 15, 2018	Adversarial TextOptical Character Recognition	—Unverified
Teaching Machines to Code: Neural Markup Generation with Visual Attention	Feb 15, 2018	MathOptical Character Recognition (OCR)	CodeCode Available
E2E-MLT - an Unconstrained End-to-End Method for Multi-Language Scene Text	Jan 30, 2018	Optical Character Recognition (OCR)	CodeCode Available

Show:10 25 50

← PrevPage 101 of 121Next →

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