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 81–90 of 1209 papers

Title	Date	Tasks	Status	Hype
Towards Calibration Enhanced Network by Inverse Adversarial Attack	Apr 8, 2025	Adversarial AttackOptical Character Recognition	—Unverified	0
Towards Visual Text Grounding of Multimodal Large Language Model	Apr 7, 2025	BenchmarkingLanguage Modeling	—Unverified	0
VISTA-OCR: Towards generative and interactive end to end OCR models	Apr 4, 2025	DecoderOptical Character Recognition (OCR)	—Unverified	0
QID: Efficient Query-Informed ViTs in Data-Scarce Regimes for OCR-free Visual Document Understanding	Apr 3, 2025	document understandingLanguage Modeling	—Unverified	0
Multimodal LLMs for OCR, OCR Post-Correction, and Named Entity Recognition in Historical Documents	Apr 1, 2025	named-entity-recognitionNamed Entity Recognition	CodeCode Available	1
Context-Independent OCR with Multimodal LLMs: Effects of Image Resolution and Visual Complexity	Mar 31, 2025	Image CaptioningOptical Character Recognition	—Unverified	0
From Panels to Prose: Generating Literary Narratives from Comics	Mar 30, 2025	Optical Character Recognition (OCR)	CodeCode Available	3
BiblioPage: A Dataset of Scanned Title Pages for Bibliographic Metadata Extraction	Mar 25, 2025	document understandingobject-detection	CodeCode Available	0
TFIC: End-to-End Text-Focused Image Compression for Coding for Machines	Mar 25, 2025	Image CompressionOptical Character Recognition	—Unverified	0
PM4Bench: A Parallel Multilingual Multi-Modal Multi-task Benchmark for Large Vision Language Model	Mar 24, 2025	Language ModelingLanguage Modelling	CodeCode Available	1

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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