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 231–240 of 1209 papers

Title	Date	Tasks	Status
Corrupted but Not Broken: Understanding and Mitigating the Negative Impacts of Corrupted Data in Visual Instruction Tuning	Feb 18, 2025	Optical Character Recognition (OCR)	—Unverified
CREPE: Coordinate-Aware End-to-End Document Parser	May 1, 2024	document understandingOptical Character Recognition (OCR)	—Unverified
CHISPA on the GO: A mobile Chinese-Spanish translation service for travellers in trouble	Apr 1, 2014	Image RetrievalInformation Retrieval	—Unverified
Convolutional Neural Networks for Automatic Meter Reading	Feb 25, 2019	Counter RecognitionData Augmentation	—Unverified
Chinese/English mixed Character Segmentation as Semantic Segmentation	Nov 7, 2016	DiversityOptical Character Recognition (OCR)	—Unverified
A random forest system combination approach for error detection in digital dictionaries	Oct 30, 2014	Language ModelingLanguage Modelling	—Unverified
A Linked Data Model for Multimodal Sentiment and Emotion Analysis	Jul 1, 2015	Emotion RecognitionOpinion Mining	—Unverified
Convolutional Neural Networks for Font Classification	Aug 11, 2017	ClassificationData Augmentation	—Unverified
ChemRxivQuest: A Curated Chemistry Question-Answer Database Extracted from ChemRxiv Preprints	May 8, 2025	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Arabic Handwritten Document OCR Solution with Binarization and Adaptive Scale Fusion Detection	Dec 2, 2024	BinarizationOptical 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