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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 221–230 of 1209 papers

Title	Date	Tasks	Status	Hype
Computer Vision Intelligence Test Modeling and Generation: A Case Study on Smart OCR	Sep 14, 2024	3D ClassificationOptical Character Recognition	—Unverified	0
PdfTable: A Unified Toolkit for Deep Learning-Based Table Extraction	Sep 8, 2024	Deep LearningDocument Layout Analysis	—Unverified	0
UNIT: Unifying Image and Text Recognition in One Vision Encoder	Sep 6, 2024	DecoderOptical Character Recognition (OCR)	—Unverified	0
Confidence-Aware Document OCR Error Detection	Sep 6, 2024	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified	0
mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding	Sep 5, 2024	document understandingGPU	—Unverified	0
MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark	Sep 4, 2024	Optical Character Recognition (OCR)	CodeCode Available	4
General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model	Sep 3, 2024	DecoderMath	CodeCode Available	9
Post-OCR Text Correction for Bulgarian Historical Documents	Aug 31, 2024	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available	0
CLOCR-C: Context Leveraging OCR Correction with Pre-trained Language Models	Aug 30, 2024	Articlesnamed-entity-recognition	CodeCode Available	0
ChartEye: A Deep Learning Framework for Chart Information Extraction	Aug 28, 2024	Chart UnderstandingClassification	—Unverified	0

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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 105M	Accuracy (%)	89.6	—	Unverified
2	DTrOCR	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