The artistic style within a painting is the means of expression, which includes not only the
painting material, colors, and brushstrokes, but also the high-level attributes, including …

Existing neural style transfer methods require reference style images to transfer texture
information of style images to content images. However, in many practical situations, users …

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 …

Although existing artistic style transfer methods have achieved significant improvement with
deep neural networks, they still suffer from artifacts such as disharmonious colors and …

In this work, we tackle the challenging problem of arbitrary image style transfer using a novel
style feature representation learning method. A suitable style representation, as a key …

Content and style (CS) disentanglement is a fundamental problem and critical challenge of
style transfer. Existing approaches based on explicit definitions (eg, Gram matrix) or implicit …

In this work, we propose a new feed-forward arbitrary style transfer method, referred to as
StyleFormer, which can simultaneously fulfill fine-grained style diversity and semantic …

This paper presents a stylized novel view synthesis method. Applying state-of-the-art
stylization methods to novel views frame by frame often causes jittering artifacts due to the …

In this work, we aim to address the 3D scene stylization problem-generating stylized images
of the scene at arbitrary novel view angles. A straightforward solution is to combine existing …

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 …