Generative adversarial networks (GANs) have been very successful for synthesizing the
images in a given dataset. The artificially generated images by GANs are very realistic. The …

Score-based diffusion models (SBDMs) have achieved the SOTA FID results in unpaired
image-to-image translation (I2I). However, we notice that existing methods totally ignore the …

Unpaired image-to-image translation has broad applications in art, design, and scientific
simulations. One early breakthrough was CycleGAN that emphasizes one-to-one map**s …

Artistic style transfer aims to repaint the content image with the learned artistic style. Existing
artistic style transfer methods can be divided into two categories: small model-based …

Transformer's recent integration into style transfer leverages its proficiency in establishing
long-range dependencies, albeit at the expense of attenuated local modeling. This paper …

In the digital age, cybercrimes, particularly cyber harassment, have become pressing issues,
targeting vulnerable individuals like children, teenagers, and women. Understanding the …

Transforming near-infrared (NIR) images into realistic RGB images is a challenging task.
Recently, with the development of deep learning, the colorization of NIR images has been …

Colorizing unpaired thermal infrared images is a challenging task that existing methods
struggle to perform effectively, often resulting in blurry details and unclear textures. To …

This article introduces a novel approach to unsupervised image-to-image translation, aiming
to overcome the limitations of existing methods in accurately capturing the shape of the …

Image-to-image translation (I2I) transforms an image from a source domain to a target
domain while preserving source content. Most computer vision applications are in the field of …