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 51–60 of 1209 papers

Title	Date	Tasks	Status	Hype
An Empirical Study of Scaling Law for Scene Text Recognition	Jan 1, 2024	Optical Character Recognition (OCR)Scene Text Recognition	CodeCode Available	2
OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models	May 13, 2023	Key Information ExtractionNutrition	CodeCode Available	2
Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding	Oct 7, 2022	Chart Question AnsweringDiversity	CodeCode Available	2
PP-OCR: A Practical Ultra Lightweight OCR System	Sep 21, 2020	Computational EfficiencyOptical Character Recognition	CodeCode Available	2
A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document Understanding	Jul 2, 2024	document understandingKey Information Extraction	CodeCode Available	2
Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want	Mar 29, 2024	Instruction FollowingLanguage Modelling	CodeCode Available	2
DTrOCR: Decoder-only Transformer for Optical Character Recognition	Aug 30, 2023	DecoderHandwritten Text Recognition	CodeCode Available	2
GUICourse: From General Vision Language Models to Versatile GUI Agents	Jun 17, 2024	Natural Language Visual GroundingOptical Character Recognition (OCR)	CodeCode Available	2
NAF-DPM: A Nonlinear Activation-Free Diffusion Probabilistic Model for Document Enhancement	Apr 8, 2024	BinarizationDocument Enhancement	CodeCode Available	2
Visually Guided Generative Text-Layout Pre-training for Document Intelligence	Mar 25, 2024	Document Classificationdocument understanding	CodeCode Available	2

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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