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 141–150 of 1209 papers

Title	Date	Tasks	Status
ERPA: Efficient RPA Model Integrating OCR and LLMs for Intelligent Document Processing	Dec 24, 2024	Optical Character RecognitionOptical Character Recognition (OCR)	—Unverified
HAUR: Human Annotation Understanding and Recognition Through Text-Heavy Images	Dec 24, 2024	Optical Character Recognition (OCR)Question Answering	—Unverified
VORTEX: A Spatial Computing Framework for Optimized Drone Telemetry Extraction from First-Person View Flight Data	Dec 24, 2024	Computational EfficiencyOptical Character Recognition	—Unverified
LMV-RPA: Large Model Voting-based Robotic Process Automation	Dec 23, 2024	Optical Character RecognitionOptical Character Recognition (OCR)	CodeCode Available
InstructOCR: Instruction Boosting Scene Text Spotting	Dec 20, 2024	Optical Character Recognition (OCR)Text Spotting	CodeCode Available
Deciphering the Underserved: Benchmarking LLM OCR for Low-Resource Scripts	Dec 20, 2024	BenchmarkingOptical Character Recognition	CodeCode Available
TextSleuth: Towards Explainable Tampered Text Detection	Dec 19, 2024	Domain GeneralizationOptical Character Recognition (OCR)	—Unverified
Track the Answer: Extending TextVQA from Image to Video with Spatio-Temporal Clues	Dec 17, 2024	Language ModelingLanguage Modelling	CodeCode Available
DoPTA: Improving Document Layout Analysis using Patch-Text Alignment	Dec 17, 2024	Document AIDocument Image Classification	—Unverified
Advanced ingestion process powered by LLM parsing for RAG system	Dec 16, 2024	Optical Character Recognition (OCR)RAG	—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	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