The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

Image inpainting is an important research direction in the study of computer vision, and is
widely used in image editing and photo inpainting etc. Traditional image inpainting …

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 …

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

Universal style transfer retains styles from reference images in content images. While
existing methods have achieved state-of-the-art style transfer performance, they are not …

Recent studies on StyleGAN show high performance on artistic portrait generation by
transfer learning with limited data. In this paper, we explore more challenging exemplar …

We present the full-resolution correspondence learning for cross-domain images, which aids
image translation. We adopt a hierarchical strategy that uses the correspondence from …

We present a method for semantically transferring the visual appearance of one natural
image to another. Specifically, our goal is to generate an image in which objects in a source …

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

Unsupervised image-to-image translation is an important and challenging problem in
computer vision. Given an image in the source domain, the goal is to learn the conditional …