Artistic text recognition is an extremely challenging task with a wide range of applications.
However, current scene text recognition methods mainly focus on irregular text while have …

Current text recognition systems, including those for handwritten scripts and scene text, have
relied heavily on image synthesis and augmentation, since it is difficult to realize real-world …

Although text recognition has significantly evolved over the years, state-of the-art (SOTA)
models still struggle in the wild scenarios due to complex backgrounds, varying fonts …

The recent focus on Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) has shifted
towards generalising a model to new categories without any training data from them. In real …

Scene text recognition is a challenging task due to the complex backgrounds and diverse
variations of text instances. In this paper, we propose a novel Semantic GAN and Balanced …

Text recognition remains a fundamental and extensively researched topic in computer
vision, largely owing to its wide array of commercial applications. The challenging nature of …

This paper looks at semi-supervised learning (SSL) for image-based text recognition. One of
the most popular SSL approaches is pseudo-labeling (PL). PL approaches assign labels to …

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 …

Document binarization is a crucial pre-processing step for various document analysis tasks.
However, existing methods fail to accurately capture stroke edges, primarily due to the …

Writing style is an abstract attribute in handwritten text. It plays an important role in
recognition systems and is not easy to define explicitly. Considering the effect of writing …