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 521–530 of 1209 papers

Title	Date	Tasks	Status	Hype
Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation	Nov 22, 2022	Optical Character Recognition (OCR)Semantic Segmentation	—Unverified	0
Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images	Nov 18, 2022	DeblurringImage Deblurring	CodeCode Available	1
Text-Aware Dual Routing Network for Visual Question Answering	Nov 17, 2022	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified	0
ChartParser: Automatic Chart Parsing for Print-Impaired	Nov 16, 2022	Optical Character Recognition (OCR)	—Unverified	0
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research	Nov 15, 2022	Continual LearningDiversity	CodeCode Available	1
A Benchmark and Dataset for Post-OCR text correction in Sanskrit	Nov 15, 2022	AstronomyOptical Character Recognition (OCR)	CodeCode Available	1
On Web-based Visual Corpus Construction for Visual Document Understanding	Nov 7, 2022	document understandingOptical Character Recognition (OCR)	CodeCode Available	1
Unsupervised Audio-Visual Lecture Segmentation	Oct 29, 2022	NavigateOptical Character Recognition (OCR)	CodeCode Available	1
Efficient few-shot learning for pixel-precise handwritten document layout analysis	Oct 27, 2022	Document Layout AnalysisFew-Shot Learning	—Unverified	0
A Late Multi-Modal Fusion Model for Detecting Hybrid Spam E-mail	Oct 26, 2022	CPUOptical Character Recognition	—Unverified	0

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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