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 781–790 of 1209 papers

Title	Date	Tasks	Status
You’ve translated it, now what?	Sep 1, 2022	Machine TranslationOptical Character Recognition (OCR)	—Unverified
An Ensemble of Neural Networks for Non-Linear Segmentation of Overlapped Cursive Script	Apr 7, 2019	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Zero-Shot Learning Based Approach For Medieval Word Recognition Using Deep-Learned Features	Oct 1, 2018	AttributeGeneralized Zero-Shot Learning	—Unverified
1 Million Captioned Dutch Newspaper Images	May 1, 2016	ArticlesData-to-Text Generation	—Unverified
Towards Self-Improvement of Diffusion Models via Group Preference Optimization	May 16, 2025	Optical Character Recognition (OCR)	—Unverified
3D Rendering Framework for Data Augmentation in Optical Character Recognition	Sep 27, 2022	Data AugmentationOptical Character Recognition	—Unverified
A Black-Box Attack on Optical Character Recognition Systems	Aug 30, 2022	Adversarial AttackBinarization	—Unverified
A BLSTM Network for Printed Bengali OCR System with High Accuracy	Aug 23, 2019	Optical Character Recognition (OCR)Vocal Bursts Intensity Prediction	—Unverified
Abstractive Information Extraction from Scanned Invoices (AIESI) using End-to-end Sequential Approach	Sep 12, 2020	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
A Classical Approach to Handcrafted Feature Extraction Techniques for Bangla Handwritten Digit Recognition	Jan 25, 2022	Handwritten Digit RecognitionOptical 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