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
Resolving Referring Expressions in Images With Labeled Elements	Oct 24, 2018	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
Resolving Sentiment Discrepancy for Multimodal Sentiment Detection via Semantics Completion and Decomposition	Jul 9, 2024	Contrastive LearningOptical Character Recognition (OCR)	—Unverified
Resource Constrained Structured Prediction	Feb 28, 2016	Dependency ParsingOptical Character Recognition	—Unverified
Resume Information Extraction via Post-OCR Text Processing	Jun 23, 2023	Object RecognitionOptical Character Recognition	—Unverified
Rethinking Visual Prompting for Multimodal Large Language Models with External Knowledge	Jul 5, 2024	Instance SegmentationOptical Character Recognition (OCR)	—Unverified
Revisiting Noise in Natural Language Processing for Computational Social Science	Mar 10, 2025	Optical Character Recognition (OCR)	—Unverified
Rich Semantic Knowledge Enhanced Large Language Models for Few-shot Chinese Spell Checking	Mar 13, 2024	Chinese Spell CheckingIn-Context Learning	—Unverified
Robustness Evaluation of Transformer-based Form Field Extractors via Form Attacks	Oct 8, 2021	FormOptical Character Recognition (OCR)	—Unverified
Robust Text CAPTCHAs Using Adversarial Examples	Jan 7, 2021	Adversarial AttackOptical Character Recognition (OCR)	—Unverified
Rosetta: Large scale system for text detection and recognition in images	Oct 11, 2019	Optical Character RecognitionOptical 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