SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 776–800 of 1209 papers

TitleStatusHype
Tablext: A Combined Neural Network And Heuristic Based Table Extractor—0
Open data for Moroccan license plates for OCR applications : data collection, labeling, and model construction—0
TeLCoS: OnDevice Text Localization with Clustering of Script—0
PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering NetworkCode0
Document Layout Analysis via Dynamic Residual Feature Fusion—0
We Live in a Motorized Civilization: Robert Moses Replies to Robert Caro—0
ICDAR2019 Competition on Scanned Receipt OCR and Information Extraction—0
Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition—0
uTHCD: A New Benchmarking for Tamil Handwritten OCR—0
Select, Substitute, Search: A New Benchmark for Knowledge-Augmented Visual Question AnsweringCode0
TS-Net: OCR Trained to Switch Between Text Transcription Styles—0
Deep Structured Feature Networks for Table Detection and Tabular Data Extraction from Scanned Financial Document Images—0
Efficient Online ML API Selection for Multi-Label Classification Tasks—0
SPAN: a Simple Predict & Align Network for Handwritten Paragraph RecognitionCode0
Post-OCR Paragraph Recognition by Graph Convolutional Networks—0
It Takes Two to Tango: Combining Visual and Textual Information for Detecting Duplicate Video-Based Bug ReportsCode0
An Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance DetectionCode0
Robust Text CAPTCHAs Using Adversarial Examples—0
On-Device Document Classification using multimodal features—0
End-to-End Piece-Wise Unwarping of Document Images—0
BROS: A Pre-trained Language Model for Understanding Texts in Document—0
NOSE Augment: Fast and Effective Data Augmentation Without Searching—0
ConvMath: A Convolutional Sequence Network for Mathematical Expression Recognition—0
Named Entity Recognition in the Legal Domain using a Pointer Generator Network—0
Indonesian ID Card Extractor Using Optical Character Recognition and Natural Language Post-Processing—0
Show:102550
← PrevPage 32 of 49Next →
All datasetsBenchmarking Chinese Text Recognition: Datasets, Baselines, and an Empirical StudyVideoDB's OCR Benchmark Public CollectionFSNS - TestI2L-140KSUTim2latex-100k

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DTrOCRAccuracy (%)89.6—Unverified
2DTrOCR 105MAccuracy (%)89.6—Unverified
3MaskOCR-LAccuracy (%)82.6—Unverified
4TransOCRAccuracy (%)72.8—Unverified
5SRNAccuracy (%)65—Unverified
6MORANAccuracy (%)64.3—Unverified
7SEEDAccuracy (%)61.2—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4oAverage Accuracy76.22—Unverified
2Gemini-1.5 ProAverage Accuracy76.13—Unverified
3Claude-3 SonnetAverage Accuracy67.71—Unverified
4RapidOCRAverage Accuracy56.98—Unverified
5EasyOCRAverage Accuracy49.3—Unverified
#ModelMetricClaimedVerifiedStatus
1STREETSequence error27.54—Unverified
2SEESequence error22—Unverified
3AttentionOCR_Inception-resnet-v2_LocationSequence error15.8—Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-NOPOOLBLEU89.09—Unverified
2I2L-STRIPSBLEU89—Unverified
#ModelMetricClaimedVerifiedStatus
1TesseractCharacter Error Rate (CER)0.08—Unverified
2EasyOCRCharacter Error Rate (CER)0.07—Unverified
#ModelMetricClaimedVerifiedStatus
1I2L-STRIPSBLEU88.86—Unverified