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 711–720 of 1209 papers

Title	Date	Tasks	Status
TextPixs: Glyph-Conditioned Diffusion with Character-Aware Attention and OCR-Guided Supervision	Jul 8, 2025	Image GenerationOptical Character Recognition (OCR)	—Unverified
Text Reading Order in Uncontrolled Conditions by Sparse Graph Segmentation	May 4, 2023	Optical Character Recognition (OCR)	—Unverified
Text Recognition in Scene Image and Video Frame using Color Channel Selection	Jul 21, 2017	Binarizationchannel selection	—Unverified
TextSR: Diffusion Super-Resolution with Multilingual OCR Guidance	May 29, 2025	Image Super-ResolutionOptical Character Recognition	—Unverified
TFIC: End-to-End Text-Focused Image Compression for Coding for Machines	Mar 25, 2025	Image CompressionOptical Character Recognition	—Unverified
The Corpora They Are a-Changing: a Case Study in Italian Newspapers	Aug 1, 2021	Optical Character Recognition (OCR)	—Unverified
The future of document indexing: GPT and Donut revolutionize table of content processing	Mar 12, 2024	Language ModelingLanguage Modelling	—Unverified
The goo300k corpus of historical Slovene	May 1, 2012	LEMMALemmatization	—Unverified
The Hidden Structure -- Improving Legal Document Understanding Through Explicit Text Formatting	May 19, 2025	document understandingOptical Character Recognition (OCR)	—Unverified
The Interplay Between Lexical and Syntactic Resources in Incremental Parsebanking	May 1, 2014	Optical Character Recognition (OCR)	—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