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

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Showing 826–850 of 1209 papers

TitleStatusHype
Finding the Evidence: Localization-aware Answer Prediction for Text Visual Question Answering—0
Hamming OCR: A Locality Sensitive Hashing Neural Network for Scene Text Recognition—0
Towards Image-based Automatic Meter Reading in Unconstrained Scenarios: A Robust and Efficient Approach—0
An Efficient Language-Independent Multi-Font OCR for Arabic Script—0
Word Segmentation from Unconstrained Handwritten Bangla Document Images using Distance Transform—0
Handwritten Script Identification from Text Lines—0
A New Approach for Texture based Script Identification At Block Level using Quad Tree Decomposition—0
Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices—0
Abstractive Information Extraction from Scanned Invoices (AIESI) using End-to-end Sequential Approach—0
MRZ code extraction from visa and passport documents using convolutional neural networksCode0
OCR Graph Features for Manipulation Detection in Documents—0
Optical Character Recognition, Word Segmentation, Sentence Segmentation, and Information Extraction for Historical and Literature Texts in Classical Chinese—0
EASTER: Efficient and Scalable Text Recognizer—0
On the Accuracy of CRNNs for Line-Based OCR: A Multi-Parameter Evaluation—0
Can You Read Me Now? Content Aware Rectification using Angle Supervision—0
Weakly Supervised Construction of ASR Systems with Massive Video Data—0
An End-to-End OCR Text Re-organization Sequence Learning for Rich-text Detail Image Comprehension—0
Advancing Visual Specification of Code Requirements for Graphs—0
Deep Learning Based Traffic Surveillance System For Missing and Suspicious Car Detection—0
Tamil Vowel Recognition With Augmented MNIST-like Data Set—0
What Machines See Is Not What They Get: Fooling Scene Text Recognition Models With Adversarial Text Images—0
Exploiter des mod\`eles de langue pour \'evaluer des sorties de logiciels d'OCR pour des documents fran du XVIIe si\`ecle ()—0
Computer Vision Toolkit for Non-invasive Monitoring of Factory Floor Artifacts—0
Quantitative Analysis of Image Classification Techniques for Memory-Constrained Devices—0
Deep Learning Based Vehicle Tracking System Using License Plate Detection And Recognition—0
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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