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 …

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 …

Abstract 3D style transfer aims to render stylized novel views of a 3D scene with multi-view
consistency. However, most existing work suffers from a three-way dilemma over accurate …

In this paper, we aim to devise a universally versatile style transfer method capable of
performing artistic, photo-realistic, and video style transfer jointly, without seeing videos …

Controllable image synthesis models allow creation of diverse images based on text
instructions or guidance from a reference image. Recently, denoising diffusion probabilistic …

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 …

We present an approach to enhancing the realism of synthetic images. The images are
enhanced by a convolutional network that leverages intermediate representations produced …