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 1076–1100 of 1209 papers

TitleStatusHype
Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation—0
Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices—0
Fast Search with Poor OCR—0
Fetch-A-Set: A Large-Scale OCR-Free Benchmark for Historical Document Retrieval—0
Financial Table Extraction in Image Documents—0
Finding Names in Trove: Named Entity Recognition for Australian Historical Newspapers—0
Finding the Evidence: Localization-aware Answer Prediction for Text Visual Question Answering—0
Finite State Approach to the Kazakh Nominal Paradigm—0
FLELex: a graded lexical resource for French foreign learners—0
Font Identification in Historical Documents Using Active Learning—0
Fooling OCR Systems with Adversarial Text Images—0
FormGym: Doing Paperwork with Agents—0
Fraunhofer SIT at CheckThat! 2023: Mixing Single-Modal Classifiers to Estimate the Check-Worthiness of Multi-Modal Tweets—0
French Word Recognition through a Quick Survey on Recurrent Neural Networks Using Long-Short Term Memory RNN-LSTM—0
From Machine Learning to Machine Reasoning—0
Efficient Online ML API Selection for Multi-Label Classification Tasks—0
Gameplay Highlights Generation—0
Generalization or Hallucination? Understanding Out-of-Context Reasoning in Transformers—0
Generalizing Analytic Shrinkage for Arbitrary Covariance Structures—0
Post-OCR Paragraph Recognition by Graph Convolutional Networks—0
Generating a Training Corpus for OCR Post-Correction Using Encoder-Decoder Model—0
Generating Monolingual Dataset for Low Resource Language Bodo from old books using Google Keep—0
Geometric Rectification of Creased Document Images based on Isometric Mapping—0
GlyphMastero: A Glyph Encoder for High-Fidelity Scene Text Editing—0
GMN: Generative Multi-modal Network for Practical Document Information Extraction—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