SOTAVerified

Handwritten Text Recognition

Handwritten Text Recognition (HTR) is the task of automatically identifying and transcribing handwritten text from images or scanned documents into machine-readable text. The goal is to develop a system capable of accurately interpreting diverse handwriting styles, accounting for variations in alignment, stroke, spacing, and noise. This task involves detecting handwritten regions within an image, extracting the text content, and converting it into a structured digital format, enabling further search, indexing, or data analysis.

Papers

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Showing 1–50 of 139 papers

TitleStatusHype
Advancing Offline Handwritten Text Recognition: A Systematic Review of Data Augmentation and Generation Techniques—0
Learning to Align: Addressing Character Frequency Distribution Shifts in Handwritten Text RecognitionCode0
MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning—0
Preserving Privacy Without Compromising Accuracy: Machine Unlearning for Handwritten Text Recognition—0
Meta-DAN: towards an efficient prediction strategy for page-level handwritten text recognitionCode1
TRIDIS: A Comprehensive Medieval and Early Modern Corpus for HTR and NER—0
Benchmarking Large Language Models for Handwritten Text Recognition—0
Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document TranscriptionCode0
Handwritten Text Recognition: A Survey—0
Col-OLHTR: A Novel Framework for Multimodal Online Handwritten Text Recognition—0
HAND: Hierarchical Attention Network for Multi-Scale Handwritten Document Recognition and Layout AnalysisCode0
HTR-JAND: Handwritten Text Recognition with Joint Attention Network and Knowledge DistillationCode0
On the Generalization of Handwritten Text Recognition Models—0
Nuremberg Letterbooks: A Multi-Transcriptional Dataset of Early 15th Century Manuscripts for Document Analysis—0
Unlocking the Archives: Using Large Language Models to Transcribe Handwritten Historical DocumentsCode2
Integrating Canonical Neural Units and Multi-Scale Training for Handwritten Text Recognition—0
Hespi: A pipeline for automatically detecting information from hebarium specimen sheetsCode1
HATFormer: Historic Handwritten Arabic Text Recognition with Transformers—0
HTR-VT: Handwritten Text Recognition with Vision TransformerCode2
Platypus: A Generalized Specialist Model for Reading Text in Various FormsCode0
DANIEL: A fast Document Attention Network for Information Extraction and Labelling of handwritten documentsCode1
Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text RecognitionCode1
Arabic Handwritten Text for Person Biometric Identification: A Deep Learning Approach—0
End-to-end information extraction in handwritten documents: Understanding Paris marriage records from 1880 to 1940—0
Revisiting N-Gram Models: Their Impact in Modern Neural Networks for Handwritten Text Recognition—0
Align, Minimize and Diversify: A Source-Free Unsupervised Domain Adaptation Method for Handwritten Text Recognition—0
GatedLexiconNet: A Comprehensive End-to-End Handwritten Paragraph Text Recognition System—0
Spatial Context-based Self-Supervised Learning for Handwritten Text Recognition—0
Best Practices for a Handwritten Text Recognition SystemCode1
Automatic Transcription of Handwritten Old Occitan LanguageCode0
Pipeline Enabling Zero-shot Classification for Bangla Handwritten Grapheme—0
Data Generation for Post-OCR correction of Cyrillic handwritingCode1
Exploring OCR Capabilities of GPT-4V(ision) : A Quantitative and In-depth EvaluationCode1
DTrOCR: Decoder-only Transformer for Optical Character RecognitionCode2
A tailored Handwritten-Text-Recognition System for Medieval Latin—0
Handwritten Stenography Recognition and the LION DatasetCode0
ReLU and Addition-based Gated RNN—0
A Transformer-based Approach for Arabic Offline Handwritten Text Recognition—0
Writer adaptation for offline text recognition: An exploration of neural network-based methodsCode0
Handwritten Text Recognition Using Convolutional Neural Network—0
Handwritten Text Recognition from Crowdsourced Annotations—0
BN-DRISHTI: Bangla Document Recognition through Instance-level Segmentation of Handwritten Text ImagesCode1
How to Choose Pretrained Handwriting Recognition Models for Single Writer Fine-Tuning—0
Large Scale Genealogical Information Extraction From Handwritten Quebec Parish Records—0
SIMARA: a database for key-value information extraction from full pages—0
An end-to-end, interactive Deep Learning based Annotation system for cursive and print English handwritten text—0
Scalable handwritten text recognition system for lexicographic sources of under-resourced languages and alphabets—0
MSdocTr-Lite: A Lite Transformer for Full Page Multi-script Handwriting Recognition—0
CSSL-MHTR: Continual Self-Supervised Learning for Scalable Multi-script Handwritten Text Recognition—0
Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and RecognitionCode0
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All datasetsIAMLAM(line-level)IAM(line-level)READ2016(line-level)BelfortREAD 2016BenthamDigital PeterHKRIAM-BIAM-DSaint Gall

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Transformer w/ CNNCER7.62—Unverified
2FPHR Paragraph Level (~145 dpi)CER6.7—Unverified
3Leaky LP CellCER6.6—Unverified
4FPHR+Aug Line Level (~145 dpi)CER6.5—Unverified
5Decouple Attention NetworkCER6.4—Unverified
6Start, Follow, ReadCER6.4—Unverified
7FPHR+Aug Paragraph Level (~145 dpi)CER6.3—Unverified
8Easter2.0CER6.21—Unverified
9HTR-VT(line-level)CER4.7—Unverified
10Transformer w/ CNN (+synth)CER4.67—Unverified
#ModelMetricClaimedVerifiedStatus
1GFCNTest CER5.2—Unverified
2TrOCRTest CER3.6—Unverified
3OrigamiNet-18Test CER3.1—Unverified
4OrigamiNet-12Test CER3.1—Unverified
5OrigamiNet-24Test CER3—Unverified
6HTR-VTTest CER2.8—Unverified
#ModelMetricClaimedVerifiedStatus
1GFCNTest CER8—Unverified
2OrigamiNet-12Test CER6—Unverified
3VANTest CER5—Unverified
4HTR-VTTest CER4.7—Unverified
5TrOCRTest CER3.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN + BLSTMTest CER4.7—Unverified
2SpanTest CER4.6—Unverified
3VANTest CER4.1—Unverified
4DANTest CER4.1—Unverified
5HTR-VTTest CER3.9—Unverified
#ModelMetricClaimedVerifiedStatus
1PyLaia (human transcriptions + random split)CER (%)10.54—Unverified
2PyLaia (human transcriptions + agreement-based split)CER (%)5.57—Unverified
3PyLaia (rover consensus + agreement-based split)CER (%)4.95—Unverified
4PyLaia (all transcriptions + agreement-based split)CER (%)4.34—Unverified
#ModelMetricClaimedVerifiedStatus
1HTR-VT(line-level)CER (%)3.9—Unverified
2DANCER (%)3.22—Unverified
#ModelMetricClaimedVerifiedStatus
1StackMix+BlotsCER1.73—Unverified
#ModelMetricClaimedVerifiedStatus
1StackMix+BlotsCER2.5—Unverified
#ModelMetricClaimedVerifiedStatus
1StackMix+BlotsCER3.49—Unverified
#ModelMetricClaimedVerifiedStatus
1StackMix+BlotsCER3.77—Unverified
#ModelMetricClaimedVerifiedStatus
1StackMix+BlotsCER3.01—Unverified
#ModelMetricClaimedVerifiedStatus
1StackMix+BlotsCER3.65—Unverified
#ModelMetricClaimedVerifiedStatus
1DANCER (%)6.46—Unverified