Browse State-of-the-Art › Handwritten Text Recognition
Handwritten Text Recognition
56 papers with code · 13 benchmarks · 14 datasets archive 2025-07-28
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.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
13 leaderboard tables shown for this task, 13 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 13 until expanded.
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
14 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
2 subtasks in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 56 papers with code (139 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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21 Sep 2021 8 repositories listed Syntology ran 0 of 6 samples · 6 unverifiedText recognition is a long-standing research problem for document digitalization.
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12 Jun 2020 8 repositories listedOn IAM we even surpass single line methods that use accurate localization information during training.
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11 Mar 2021 5 repositories listedWe present a Neural Network based Handwritten Text Recognition (HTR) model architecture that can be trained to recognize full pages of handwritten or printed text without image segmentation.
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21 Dec 2019 5 repositories listedTo remedy this issue, we propose a decoupled attention network (DAN), which decouples the alignment operation from using historical decoding results.
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23 Mar 2020 3 repositories listed Syntology ran 2 of 15 samples · 13 unverifiedThis is especially true for handwritten text recognition (HTR), where each author has a unique style, unlike printed text, where the variation is smaller by design.
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13 Sep 2024 2 repositories listedTo address this limitation, we introduce a data-efficient ViT method that uses only the encoder of the standard transformer.
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13 Jun 2024 2 repositories listedWe present the Manuscripts of Handwritten Arabic~(Muharaf) dataset, which is a machine learning dataset consisting of more than 1, 600 historic handwritten page images transcribed by experts in archival Arabic.
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27 Nov 2023 2 repositories listedWe apply a Handwritten Text Recognition (HTR) model to this dataset to identify OCR errors, forming the basis for our POC model training.
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10 Mar 2023 2 repositories listedThe pressing need for digitization of historical documents has led to a strong interest in designing computerised image processing methods for automatic handwritten text recognition.
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16 Mar 2021 2 repositories listedThis paper presents a new dataset of Peter the Great's manuscripts and describes a segmentation procedure that converts initial images of documents into the lines.
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20 Dec 2020 2 repositories listedWe propose a framework for sequence-to-sequence contrastive learning (SeqCLR) of visual representations, which we apply to text recognition.
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4 Apr 2025 1 repository listedRecent advances in text recognition led to a paradigm shift for page-level recognition, from multi-step segmentation-based approaches to end-to-end attention-based ones.
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27 Feb 2025 1 repository listedExperiments on a multi-page version of the IAM Handwriting Database demonstrate that '+first page' improves transcription accuracy, balances cost with performance, and even enhances results on out-of-sample text by…
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2 Nov 2024 1 repository listedThis study demonstrates that Large Language Models (LLMs) can transcribe historical handwritten documents with significantly higher accuracy than specialized Handwritten Text Recognition (HTR) software, while being…
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11 Oct 2024 1 repository listedWe applied advanced computer vision techniques to develop the `Hespi' (HErbarium Specimen sheet PIpeline), which extracts a pre-catalogue subset of collection data on the institutional labels on herbarium specimens from…
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27 Aug 2024 1 repository listedRecently, generalist models (such as GPT-4V), trained on tremendous data in a unified way, have shown enormous potential in reading text in various scenarios, but with the drawbacks of limited accuracy and low…
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12 Jul 2024 1 repository listedDespite this, these integrated approaches have not yet matched the performance of language models, when applied to information extraction in plain text.
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17 Apr 2024 1 repository listedHandwritten text recognition has been developed rapidly in the recent years, following the rise of deep learning and its applications.
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6 Dec 2023 1 repository listedWhile existing neural network-based approaches have shown promising results in Handwritten Text Recognition (HTR) for high-resource languages and standardized/machine-written text, their application to low-resource…
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25 Oct 2023 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)We assess the model's performance across a range of OCR tasks, including scene text recognition, handwritten text recognition, handwritten mathematical expression recognition, table structure recognition, and…
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30 Aug 2023 1 repository listedTypical text recognition methods rely on an encoder-decoder structure, in which the encoder extracts features from an image, and the decoder produces recognized text from these features.
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15 Aug 2023 1 repository listedMethods: A state-of-the-art text recognition model is trained to establish a baseline.
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11 Jul 2023 1 repository listedIn this paper, we explore how HTR models can be made writer adaptive by using only a handful of examples from a new writer (e.
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31 May 2023 1 repository listedHandwriting recognition remains challenging for some of the most spoken languages, like Bangla, due to the complexity of line and word segmentation brought by the curvilinear nature of writing and lack of quality…
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25 Jan 2023 1 repository listedRecent advances in handwritten text recognition enabled to recognize whole documents in an end-to-end way: the Document Attention Network (DAN) recognizes the characters one after the other through an attention-based…
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14 Jan 2023 1 repository listedThe evaluation of Handwritten Text Recognition (HTR) systems has traditionally used metrics based on the edit distance between HTR and ground truth (GT) transcripts, at both the character and word levels.
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15 Dec 2022 1 repository listedWe use a semantic module in an encoder-decoder framework for extracting global semantic information to recognize the Indic handwritten texts.
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30 Sep 2022 1 repository listedWe proposed an approach at the line level, based on a fully convolutional network, in order to design a first generic feature extraction step for the handwriting recognition task.
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1 Jun 2022 1 repository listedThe overall aim of this paper is to assess HTR for old Greek manuscripts.
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30 May 2022 1 repository listedIn addition to the Easter2.
Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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