This paper presents a survey of image synthesis and editing with Generative Adversarial
Networks (GANs). GANs consist of two deep networks, a generator and a discriminator …

To recover the corrupted pixels, traditional inpainting methods based on low-rank priors
generally need to solve a convex optimization problem by an iterative singular value …

Distinguishing between natural images (NIs) and computer-generated (CG) images by
naked human eyes is difficult. In this paper, we propose an effective method based on a …

We propose a novel video inpainting algorithm that simultaneously hallucinates missing
appearance and motion (optical flow) information, building upon the recent'Deep Image …

We investigate the use of neural fields for modelling diverse mesoscale structures, such as
fur, fabric and grass. Instead of using classical graphics primitives to model the structure, we …

We present GenMM, a generative model that" mines" as many diverse motions as possible
from a single or few example sequences. In stark contrast to existing data-driven methods …

We present CoGS, a novel method for the style-conditioned, sketch-driven synthesis of
images. CoGS enables exploration of diverse appearance possibilities for a given sketched …

Artistically controlling fluids has always been a challenging task. Optimization techniques
rely on approximating simulation states towards target velocity or density field …

Creating realistic 3D hairs that closely match the real-world inputs remains challenging. With
the increasing popularity of lightweight depth cameras featured in devices such as iPhone X …

With the recent tremendous advances of computer graphics rendering and image editing
technologies, computergenerated fake images, which in general do not reflect what …