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 1011–1020 of 1209 papers

Title	Date	Tasks	Status
COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images	Jan 26, 2016	DiversityGeneral Classification	CodeCode Available
KL3M Tokenizers: A Family of Domain-Specific and Character-Level Tokenizers for Legal, Financial, and Preprocessing Applications	Mar 21, 2025	16k4k	CodeCode Available
Clustering-Based Article Identification in Historical Newspapers	Jun 1, 2019	ArticlesClustering	CodeCode Available
It Takes Two to Tango: Combining Visual and Textual Information for Detecting Duplicate Video-Based Bug Reports	Jan 22, 2021	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available
Optical Character Recognition of 19th Century Classical Commentaries: the Current State of Affairs	Oct 13, 2021	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available
A Multi-Object Rectified Attention Network for Scene Text Recognition	Jan 10, 2019	DecoderObject	CodeCode Available
Teaching Machines to Code: Neural Markup Generation with Visual Attention	Feb 15, 2018	MathOptical Character Recognition (OCR)	CodeCode Available
An Unsupervised Model of Orthographic Variation for Historical Document Transcription	Jun 1, 2016	Optical Character Recognition (OCR)	CodeCode Available
LAREX - A semi-automatic open-source Tool for Layout Analysis and Region Extraction on Early Printed Books	Jan 20, 2017	Optical Character Recognition (OCR)	CodeCode Available
Toward Advancing License Plate Super-Resolution in Real-World Scenarios: A Dataset and Benchmark	May 9, 2025	License Plate RecognitionOptical Character Recognition	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