Fast arbitrary neural style transfer has attracted widespread attention from academic,
industrial and art communities due to its flexibility in enabling various applications. Existing …

The goal of image style transfer is to render an image with artistic features guided by a style
reference while maintaining the original content. Owing to the locality in convolutional neural …

Large-scale text-to-image models pre-trained on massive text-image pairs show excellent
performance in image synthesis recently. However, image can provide more intuitive visual …

Artistic style transfer is an image editing task that aims at repainting everyday photographs
with learned artistic styles. Existing methods learn styles from either a single style example …

The field of neural style transfer has experienced a surge of research exploring different
avenues ranging from optimization-based approaches and feed-forward models to meta …

Multiple marginal matching problem aims at learning map**s to match a source domain to
multiple target domains and it has attracted great attention in many applications, such as …

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 …

Image style transfer aims to transfer the styles of artworks onto arbitrary photographs to
create novel artistic images. Although style transfer is inherently an underdetermined …

This paper addresses the complex issue of one-shot face stylization focusing on the
simultaneous consideration of appearance and structure where previous methods have …

Artistic style transfer aims to create new artistic images by rendering a given photograph with
the target artistic style. Existing methods learn styles simply based on global statistics or …