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 351–360 of 1209 papers

Title	Date	Tasks	Status
DocSum: Domain-Adaptive Pre-training for Document Abstractive Summarization	Dec 11, 2024	Abstractive Text SummarizationDecision Making	—Unverified
DocVLM: Make Your VLM an Efficient Reader	Dec 11, 2024	document understandingOptical Character Recognition (OCR)	—Unverified
Verb Mirage: Unveiling and Assessing Verb Concept Hallucinations in Multimodal Large Language Models	Dec 6, 2024	HallucinationOptical Character Recognition (OCR)	—Unverified
SynFinTabs: A Dataset of Synthetic Financial Tables for Information and Table Extraction	Dec 5, 2024	ArticlesDataset Generation	CodeCode Available
Aligned Music Notation and Lyrics Transcription	Dec 5, 2024	Language ModelingLanguage Modelling	CodeCode Available
Text Change Detection in Multilingual Documents Using Image Comparison	Dec 5, 2024	BinarizationChange Detection	—Unverified
CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy	Dec 3, 2024	HallucinationKey Information Extraction	—Unverified
Arabic Handwritten Document OCR Solution with Binarization and Adaptive Scale Fusion Detection	Dec 2, 2024	BinarizationOptical Character Recognition (OCR)	—Unverified
DLaVA: Document Language and Vision Assistant for Answer Localization with Enhanced Interpretability and Trustworthiness	Nov 29, 2024	Optical Character Recognition (OCR)Question Answering	CodeCode Available
VARCO-VISION: Expanding Frontiers in Korean Vision-Language Models	Nov 28, 2024	Language ModelingLanguage Modelling	—Unverified

Show:10 25 50

← PrevPage 36 of 121Next →

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