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 1091–1100 of 1209 papers

Title	Date	Tasks	Status
PopEval: A Character-Level Approach to End-To-End Evaluation Compatible with Word-Level Benchmark Dataset	Aug 29, 2019	Optical Character Recognition (OCR)	CodeCode Available
Mining Spatio-temporal Data on Industrialization from Historical Registries	Dec 3, 2016	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available
DELINE8K: A Synthetic Data Pipeline for the Semantic Segmentation of Historical Documents	Apr 30, 2024	8kDiversity	CodeCode Available
Post-OCR parsing: building simple and robust parser via BIO tagging	Sep 14, 2019	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available
Post-OCR Text Correction for Bulgarian Historical Documents	Aug 31, 2024	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available
An efficient way for segmentation of Bangla characters in printed document using curved scanning	May 13, 2016	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available
DeepErase: Weakly Supervised Ink Artifact Removal in Document Text Images	Oct 15, 2019	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available
Deciphering the Underserved: Benchmarking LLM OCR for Low-Resource Scripts	Dec 20, 2024	BenchmarkingOptical Character Recognition	CodeCode Available
When Vision Fails: Text Attacks Against ViT and OCR	Jun 12, 2023	Optical Character Recognition (OCR)	CodeCode Available
Predicting the Past: Estimating Historical Appraisals with OCR and Machine Learning	May 30, 2025	Optical Character Recognition (OCR)	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