Handwriting generation
11 papers with code • 0 benchmarks • 10 datasets
The inverse of handwriting recognition. From text generate and image of handwriting (offline) of trajectory of handwriting (online).
Benchmarks
These leaderboards are used to track progress in Handwriting generation
Most implemented papers
HyperNetworks
This work explores hypernetworks: an approach of using a one network, also known as a hypernetwork, to generate the weights for another network.
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
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.
Diffusion models for Handwriting Generation
In this paper, we propose a diffusion probabilistic model for handwriting generation.
Disentangling Writer and Character Styles for Handwriting Generation
In light of this, we propose to disentangle the style representations at both writer and character levels from individual handwritings to synthesize realistic stylized online handwritten characters.
Data Generation for Post-OCR correction of Cyrillic handwriting
We apply a Handwritten Text Recognition (HTR) model to this dataset to identify OCR errors, forming the basis for our POC model training.
Professor Forcing: A New Algorithm for Training Recurrent Networks
We introduce the Professor Forcing algorithm, which uses adversarial domain adaptation to encourage the dynamics of the recurrent network to be the same when training the network and when sampling from the network over multiple time steps.
DeepWriting: Making Digital Ink Editable via Deep Generative Modeling
Digital ink promises to combine the flexibility and aesthetics of handwriting and the ability to process, search and edit digital text.
Text and Style Conditioned GAN for Generation of Offline Handwriting Lines
This paper presents a GAN for generating images of handwritten lines conditioned on arbitrary text and latent style vectors.
WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models
Our proposed method is able to generate realistic word image samples from different writer styles, by using class index styles and text content prompts without the need of adversarial training, writer recognition, or text recognition.
Rethinking HTG Evaluation: Bridging Generation and Recognition
In this work, we introduce three measures tailored for HTG evaluation, $ \text{HTG}_{\text{HTR}} $, $ \text{HTG}_{\text{style}} $, and $ \text{HTG}_{\text{OOV}} $, and argue that they are more expedient to evaluate the quality of generated handwritten images.