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 411–420 of 1209 papers

Title	Date	Tasks	Status	Hype
Optimal Projections for Discriminative Dictionary Learning using the JL-lemma	Aug 27, 2023	Dictionary LearningDimensionality Reduction	CodeCode Available	0
Bengali Document Layout Analysis with Detectron2	Aug 26, 2023	Data AugmentationDocument Layout Analysis	—Unverified	0
DISGO: Automatic End-to-End Evaluation for Scene Text OCR	Aug 25, 2023	Machine TranslationOptical Character Recognition	—Unverified	0
Nougat: Neural Optical Understanding for Academic Documents	Aug 25, 2023	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available	5
American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers	Aug 24, 2023	ArticlesLanguage Modeling	—Unverified	0
CNN based Cuneiform Sign Detection Learned from Annotated 3D Renderings and Mapped Photographs with Illumination Augmentation	Aug 22, 2023	Optical Character Recognition (OCR)	—Unverified	0
bbOCR: An Open-source Multi-domain OCR Pipeline for Bengali Documents	Aug 21, 2023	distortion correctionOptical Character Recognition	CodeCode Available	1
BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions	Aug 19, 2023	MMEOptical Character Recognition (OCR)	CodeCode Available	2
OCR Language Models with Custom Vocabularies	Aug 18, 2023	DecoderLanguage Modeling	—Unverified	0
FashionLOGO: Prompting Multimodal Large Language Models for Fashion Logo Embeddings	Aug 17, 2023	Image RetrievalLogo Recognition	CodeCode Available	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	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