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 331–340 of 1209 papers

Title	Date	Tasks	Status
A Generic Method for Automatic Ground Truth Generation of Camera-captured Documents	May 4, 2016	ArticlesOptical Character Recognition (OCR)	—Unverified
A Comparative Study of Filtering Approaches Applied to Color Archival Document Images	Aug 16, 2019	DenoisingImage Enhancement	—Unverified
BLPnet: A new DNN model and Bengali OCR engine for Automatic License Plate Recognition	Feb 18, 2022	License Plate RecognitionManagement	—Unverified
An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning	Feb 9, 2023	ObjectOptical Character Recognition (OCR)	—Unverified
BIOfid Dataset: Publishing a German Gold Standard for Named Entity Recognition in Historical Biodiversity Literature	Nov 1, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
A New Approach for Texture based Script Identification At Block Level using Quad Tree Decomposition	Sep 16, 2020	Optical Character Recognition (OCR)Tree Decomposition	—Unverified
A Compositional Textual Model for Recognition of Imperfect Word Images	Nov 27, 2018	Optical Character Recognition (OCR)Printed Text Recognition	—Unverified
Bidirectional Trained Tree-Structured Decoder for Handwritten Mathematical Expression Recognition	Dec 31, 2023	DecoderLanguage Modeling	—Unverified
A free and open-source tool that reads movie subtitles aloud	Jun 1, 2012	Optical Character Recognition (OCR)	—Unverified
DoPTA: Improving Document Layout Analysis using Patch-Text Alignment	Dec 17, 2024	Document AIDocument Image Classification	—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