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 …

We present a method for transferring the artistic features of an arbitrary style image to a 3D
scene. Previous methods that perform 3D stylization on point clouds or meshes are sensitive …

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 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 …

An authoritative, accessible, and up-to-date treatment of deep learning that strikes a
pragmatic middle ground between theory and practice. Deep learning is a fast-moving field …

Remarkable achievements have been attained with Generative Adversarial Networks
(GANs) in image-to-image translation. However, due to a tremendous amount of parameters …

State-of-the-art parametric and non-parametric style transfer approaches are prone to either
distorted local style patterns due to global statistics alignment, or unpleasing artifacts …