The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

GAN's are playing an important role in creating and generating a new set of data from the
previously available content. GAN models are impressive in the results for image and video …

You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

Optical character recognition (OCR) systems performance have improved significantly in the
deep learning era. This is especially true for handwritten text recognition (HTR), where each …

Generating synthetic images of handwritten text in a writer-specific style is a challenging
task, especially in the case of unseen styles and new words, and even more when these …

This paper presents a GAN for generating images of handwritten lines conditioned on
arbitrary text and latent style vectors. Unlike prior work, which produce stroke points or single …

The study of ancient writings has great value for archaeology and philology. Essential forms
of material are photographic characters, but manual photographic character recognition is …

In this paper, we propose a novel method for handwritten text generation that uses a style
encoder based on a vision transformer network that encodes handwriting style from …

Styled Handwritten Text Generation (HTG) has received significant attention in recent years,
propelled by the success of learning-based solutions employing GANs, Transformers, and …

This paper introduces a new publicly available image-based Swedish historical handwritten
character and word dataset named Character Arkiv Digital Sweden (CArDIS)(https …