Artistic text generation aims to amplify the aesthetic qualities of text while maintaining
readability. It can make the text more attractive and better convey its expression, thus …

A large number of annotated training images is crucial for training successful scene text
recognition models. However, collecting sufficient datasets can be a labor-intensive and …

Sequence generation models have recently made significant progress in unifying various
vision tasks. Although some auto-regressive models have demonstrated promising results in …

Recently, diffusion-based image generation methods are credited for their remarkable text-to-
image generation capabilities, while still facing challenges in accurately generating …

Abstract The paper presents CoFormer (Convolutional Fourier Transformer), a robust and
adaptable transformer architecture designed for a range of scene text tasks. CoFormer …

We propose and formulate the task of cross-language scene text editing, modifying the text
content of a scene image into new text in another language, while preserving the scene text …

In recent years, there have been significant breakthroughs in style transfer that show
impressive results, enabling the automatic creation of high-quality and diverse images …

Scene text editing (STE) aims to modify the text in the scene image to the target text while
retaining the original style. Existing models are based on GAN, where the source image and …

Scene text editing aims to modify texts on images while maintaining the style of newly
generated text similar to the original. Given an image, a target area, and target text, the task …

Text, which is regarded as one of the important clues for visual recognition, can provide rich
and accurate high-level semantic information. Therefore, the detection and recognition of …