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 261–270 of 1209 papers

Title	Date	Tasks	Status
ChartEye: A Deep Learning Framework for Chart Information Extraction	Aug 28, 2024	Chart UnderstandingClassification	—Unverified
Chart-based Reasoning: Transferring Capabilities from LLMs to VLMs	Mar 19, 2024	Chart Question AnsweringOptical Character Recognition (OCR)	—Unverified
A preliminary study on similarity-preserving digital book identifiers	Jul 1, 2015	Optical 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
Chargrid-OCR: End-to-end Trainable Optical Character Recognition for Printed Documents using Instance Segmentation	Sep 10, 2019	GPUInstance Segmentation	—Unverified
Applying BLAST to Text Reuse Detection in Finnish Newspapers and Journals, 1771-1910	May 1, 2017	Optical Character Recognition (OCR)	—Unverified
A Black-Box Attack on Optical Character Recognition Systems	Aug 30, 2022	Adversarial AttackBinarization	—Unverified
Derivate-based Component-Trees for Multi-Channel Image Segmentation	May 4, 2017	Image SegmentationOptical Character Recognition (OCR)	—Unverified
Development of a WAZOBIA-Named Entity Recognition System	May 10, 2025	Machine Translationnamed-entity-recognition	—Unverified
Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction	Nov 14, 2019	Homography EstimationOptical Character Recognition	—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