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 471–480 of 1209 papers

Title	Date	Tasks	Status
ExTTNet: A Deep Learning Algorithm for Extracting Table Texts from Invoice Images	Feb 3, 2024	Optical Character RecognitionOptical Character Recognition (OCR)	—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
Extraction of Line Word Character Segments Directly from Run Length Compressed Printed Text Documents	Mar 30, 2014	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
From Machine Learning to Machine Reasoning	Feb 9, 2011	BIG-bench Machine LearningLanguage Modeling	—Unverified
Chart-based Reasoning: Transferring Capabilities from LLMs to VLMs	Mar 19, 2024	Chart Question AnsweringOptical Character Recognition (OCR)	—Unverified
Extracting Weighted Language Lexicons from Wikipedia	May 1, 2016	ArticlesInformation Retrieval	—Unverified
Extracting structured data from invoices	Dec 1, 2018	BIG-bench Machine LearningOptical Character Recognition (OCR)	—Unverified
Chargrid-OCR: End-to-end trainable Optical Character Recognition through Semantic Segmentation and Object Detection	Sep 14, 2019	GPUobject-detection	—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