This paper surveys the state-of-the-art of research in patch-based synthesis. Patch-based
methods synthesize output images by copying small regions from exemplar imagery. This …

We tackle the problem of texture synthesis in the setting where many input images are given
and a large-scale output is required. We build on recent generative adversarial networks …

We introduce a novel approach to example-based stylization of portrait videos that
preserves both the subject's identity and the visual richness of the input style exemplar …

We present an interactive approach to synthesizing realistic variations in facial hair in
images, ranging from subtle edits to existing hair to the addition of complex and challenging …

We propose Neural Brushstroke Engine, the first method to apply deep generative models to
learn a distribution of interactive drawing tools. Our conditional GAN model learns the latent …

Markov random fields (MRFs) are the cornerstone of classical approaches to example-
based texture synthesis. Yet, it is not fully valued in the deep learning era. This paper aims to …

This paper addresses the challenge of example-based non-stationary texture synthesis. We
introduce a novel two-step approach wherein users first modify a reference texture using …

The development of deep learning algorithms has prompted many attempts to apply AI
(Artificial Intelligence) to artistic creation in the last decade. It has been observed that the …

We present a technique that leverages 2D generative diffusion models (DMs) for interactive
texture painting on the surface of 3D meshes. Unlike existing texture painting systems, our …

We review recent methods in 2D creative pattern generation and their control mechanisms,
focusing on procedural methods. The review is motivated by an artist's perspective and …