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 621–630 of 1209 papers

Title	Date	Tasks	Status
Sequence-to-Label Script Identification for Multilingual OCR	Aug 15, 2017	Optical Character Recognition (OCR)	—Unverified
Sequence to Sequence Learning for Optical Character Recognition	Nov 13, 2015	DecoderGeneral Classification	—Unverified
Sequence-to-Sequence Pre-training with Unified Modality Masking for Visual Document Understanding	May 16, 2023	Decoderdocument understanding	—Unverified
Shakti-VLMs: Scalable Vision-Language Models for Enterprise AI	Feb 24, 2025	document understandingMultimodal Reasoning	—Unverified
Similar Document Template Matching Algorithm	Nov 21, 2023	Fraud DetectionOptical Character Recognition (OCR)	—Unverified
Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps	Dec 9, 2020	DecoderImage Captioning	—Unverified
Simple Transparent Adversarial Examples	May 20, 2021	Image Generationobject-detection	—Unverified
Simulation d’erreurs d’OCR dans les systèmes de TAL pour le traitement de données anachroniques (Simulation of OCR errors in NLP systems for processing anachronistic data)	Jun 1, 2022	Optical Character Recognition (OCR)	—Unverified
Sinica-IASL Chinese spelling check system at Sighan-7	Oct 1, 2013	Optical Character Recognition (OCR)	—Unverified
SIS@IIITH at SemEval-2020 Task 8: An Overview of Simple Text Classification Methods for Meme Analysis	Dec 1, 2020	ClassificationOptical 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 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