Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

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 …

Modern 3D-GANs synthesize geometry and texture by training on large-scale datasets with
a consistent structure. Training such models on stylized, artistic data, with often unknown …

With the rapid development of cartoon industry, various studies on two-dimensional (2D)
cartoon have been proposed for different application scenarios, such as quality assessment …

In this paper we democratise caricature generation empowering individuals to effortlessly
craft personalised caricatures with just a photo and a conceptual sketch. Our objective is to …

Facial Landmark detection in natural images is a very active research domain. Impressive
progress has been made in recent years, with the rise of neural-network based methods and …

We propose, WarpGAN, a fully automatic network that can generate caricatures given an
input face photo. Besides transferring rich texture styles, WarpGAN learns to automatically …

Recent years have witnessed increasing attention in cartoon media, powered by the strong
demands of industrial applications. As the first step to understand this media, cartoon face …

Abstract 3D face reconstruction is the most captivating topic in biometrics with the advent of
deep learning and readily available graphical processing units. This paper explores the …

We investigate GAN inversion problems of using pre-trained GANs to reconstruct real
images. Recent methods for such problems typically employ a VGG perceptual loss to …