Handwritten Text Recognition

37 papers with code • 9 benchmarks • 10 datasets

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Most implemented papers

Full Page Handwriting Recognition via Image to Sequence Extraction

kingyiusuen/image-to-latex 11 Mar 2021

We 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.

Decoupled Attention Network for Text Recognition

Canjie-Luo/Scene-Text-Image-Transformer 21 Dec 2019

To remedy this issue, we propose a decoupled attention network (DAN), which decouples the alignment operation from using historical decoding results.

ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation

amzn/convolutional-handwriting-gan CVPR 2020

This 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.

Sequence-to-Sequence Contrastive Learning for Text Recognition

amazon-science/semimtr-text-recognition CVPR 2021

We propose a framework for sequence-to-sequence contrastive learning (SeqCLR) of visual representations, which we apply to text recognition.

Digital Peter: Dataset, Competition and Handwriting Recognition Methods

MarkPotanin/DigitalPeter 16 Mar 2021

This 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.

TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models

microsoft/unilm 21 Sep 2021

Text recognition is a long-standing research problem for document digitalization.

Character-Based Handwritten Text Transcription with Attention Networks

jvpoulos/Attention-OCR 11 Dec 2017

When the sequence alignment is one-to-one, softmax attention is able to learn a more precise alignment at each step of the decoding, whereas the alignment generated by sigmoid attention is much less precise.

Start, Follow, Read: End-to-End Full-Page Handwriting Recognition

cwig/start_follow_read ECCV 2018

Despite decades of research, offline handwriting recognition (HWR) of degraded historical documents remains a challenging problem, which if solved could greatly improve the searchability of online cultural heritage archives.

No Padding Please: Efficient Neural Handwriting Recognition

gwenniger/multi-hare 28 Feb 2019

Neural handwriting recognition (NHR) is the recognition of handwritten text with deep learning models, such as multi-dimensional long short-term memory (MDLSTM) recurrent neural networks.

Manifold Mixup improves text recognition with CTC loss

simplify23/Ultra_light_OCR_No.11 11 Mar 2019

Modern handwritten text recognition techniques employ deep recurrent neural networks.