Can a generative model be trained to produce images from a specific domain, guided only
by a text prompt, without seeing any image? In other words: can an image generator be …

Generating high-quality and diverse human images is an important yet challenging task in
vision and graphics. However, existing generative models often fall short under the high …

One-shot talking face generation aims at synthesizing a high-quality talking face video from
an arbitrary portrait image, driven by a video or an audio segment. In this work, we provide a …

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 …

Generating high-quality artistic portrait videos is an important and desirable task in computer
graphics and vision. Although a series of successful portrait image toonification models built …

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 …

Unsupervised generation of clothed virtual humans with various appearance and
animatable poses is important for creating 3D human avatars and other AR/VR applications …

Abstract Generative Adversarial Networks (GANs) have established themselves as a
prevalent approach to image synthesis. Of these, StyleGAN offers a fascinating case study …

Automatic high-quality rendering of anime scenes from complex real-world images is of
significant practical value. The challenges of this task lie in the complexity of the scenes, the …