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 51–100 of 139 papers

TitleStatusHype
SPAN: a Simple Predict & Align Network for Handwritten Paragraph RecognitionCode0
Uncovering the Handwritten Text in the Margins: End-to-end Handwritten Text Detection and RecognitionCode0
End-to-end Handwritten Paragraph Text Recognition Using a Vertical Attention NetworkCode0
Handwritten Paleographic Greek Text Recognition: A Century-Based ApproachCode0
Start, Follow, Read: End-to-End Full-Page Handwriting RecognitionCode0
Handwritten Stenography Recognition and the LION DatasetCode0
End-to-End Page-Level Assessment of Handwritten Text RecognitionCode0
Character-Based Handwritten Text Transcription with Attention NetworksCode0
Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image EnhancementCode0
Pay Attention to What You Read: Non-recurrent Handwritten Text-Line Recognition—0
Pipeline Enabling Zero-shot Classification for Bangla Handwritten Grapheme—0
Preserving Privacy Without Compromising Accuracy: Machine Unlearning for Handwritten Text Recognition—0
Recurrent neural network transducer for Japanese and Chinese offline handwritten text recognition—0
Regular expressions for decoding of neural network outputs—0
ReLU and Addition-based Gated RNN—0
Rethinking Text Line Recognition Models—0
Revisiting N-Gram Models: Their Impact in Modern Neural Networks for Handwritten Text Recognition—0
Scalable handwritten text recognition system for lexicographic sources of under-resourced languages and alphabets—0
Self-Training of Handwritten Word Recognition for Synthetic-to-Real Adaptation—0
SIMARA: a database for key-value information extraction from full pages—0
2D Self-Organized ONN Model For Handwritten Text Recognition—0
Synthetic data generation for Indic handwritten text recognition—0
The Challenges of HTR Model Training: Feedback from the Project Donner le gout de l'archive a l'ere numerique—0
The LAM Dataset: A Novel Benchmark for Line-Level Handwritten Text Recognition—0
Towards Robust Handwritten Text Recognition with On-the-fly User Participation—0
TRIDIS: A Comprehensive Medieval and Early Modern Corpus for HTR and NER—0
Unsupervised Adaptation for Synthetic-to-Real Handwritten Word Recognition—0
Urdu Handwritten Text Recognition Using ResNet18—0
Variational Connectionist Temporal Classification—0
Vital Records: Uncover the past from historical handwritten records—0
Spatial Context-based Self-Supervised Learning for Handwritten Text Recognition—0
A Computationally Efficient Pipeline Approach to Full Page Offline Handwritten Text Recognition—0
Advancing Offline Handwritten Text Recognition: A Systematic Review of Data Augmentation and Generation Techniques—0
A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts—0
A Lexicon and Depth-wise Separable Convolution Based Handwritten Text Recognition System—0
Align, Minimize and Diversify: A Source-Free Unsupervised Domain Adaptation Method for Handwritten Text Recognition—0
A limited-size ensemble of homogeneous CNN/LSTMs for high-performance word classification—0
An Alternative Deep Feature Approach to Line Level Keyword Spotting—0
An Efficient End-to-End Neural Model for Handwritten Text Recognition—0
An end-to-end, interactive Deep Learning based Annotation system for cursive and print English handwritten text—0
An LDA-based Topic Selection Approach to Language Model Adaptation for Handwritten Text Recognition—0
Applications of Machine Learning in Document Digitisation—0
Arabic Handwritten Text for Person Biometric Identification: A Deep Learning Approach—0
Are 2D-LSTM really dead for offline text recognition?—0
A Scalable Handwritten Text Recognition System—0
A Study of Augmentation Methods for Handwritten Stenography Recognition—0
A tailored Handwritten-Text-Recognition System for Medieval Latin—0
A Transformer-based Approach for Arabic Offline Handwritten Text Recognition—0
BADAM: A Public Dataset for Baseline Detection in Arabic-script Manuscripts—0
Bench-Marking Information Extraction in Semi-Structured Historical Handwritten Records—0
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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
5Start, Follow, ReadCER6.4—Unverified
6Decouple Attention NetworkCER6.4—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
3DANTest CER4.1—Unverified
4VANTest 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