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 21–30 of 1209 papers

Title	Date	Tasks	Status	Hype	Score
PaliGemma 2: A Family of Versatile VLMs for Transfer	Dec 4, 2024	Language ModelingLanguage Modelling	CodeCode Available	3	5
MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities	Aug 1, 2024	MathMM-Vet	CodeCode Available	3	5
OCR-free Document Understanding Transformer	Nov 30, 2021	Document Image Classificationdocument understanding	CodeCode Available	3	5
Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion	Dec 5, 2024	Contrastive LearningHallucination	CodeCode Available	3	5
IMKGA-SM: Interpretable Multimodal Knowledge Graph Answer Prediction via Sequence Modeling	Jan 6, 2023	Link PredictionOptical Character Recognition	CodeCode Available	2	5
GlyphDraw: Seamlessly Rendering Text with Intricate Spatial Structures in Text-to-Image Generation	Mar 31, 2023	Image GenerationOptical Character Recognition (OCR)	CodeCode Available	2	5
GlyphControl: Glyph Conditional Control for Visual Text Generation	May 29, 2023	Optical Character Recognition (OCR)Text Generation	CodeCode Available	2	5
GUICourse: From General Vision Language Models to Versatile GUI Agents	Jun 17, 2024	Natural Language Visual GroundingOptical Character Recognition (OCR)	CodeCode Available	2	5
General Detection-based Text Line Recognition	Sep 25, 2024	HTROptical Character Recognition (OCR)	CodeCode Available	2	5
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining	Jan 1, 2025	Optical Character Recognition (OCR)	CodeCode Available	2	5

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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