To ensure good performance, modern machine learning models typically require large
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …

Abstract 3D reconstruction of deformable (or non‐rigid) scenes from a set of monocular 2D
image observations is a long‐standing and actively researched area of computer vision and …

We address the problem of learning person-specific facial priors from a small number (eg,
20) of portrait photos of the same person. This enables us to edit this specific person's facial …

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

Generative models aim to learn the distribution of observed data by generating new
instances. With the advent of neural networks, deep generative models, including variational …

Recent work has shown the possibility of training generative models of 3D content from 2D
image collections on small datasets corresponding to a single object class, such as human …

In this paper, we address the challenging problem of 3D toonification, which involves
transferring the style of an artistic domain onto a target 3D face with stylized geometry and …

Generating large-scale 3D scenes cannot simply apply existing 3D object synthesis
technique since 3D scenes usually hold complex spatial configurations and consist of a …

Recent years have seen remarkable progress in deep learning powered visual content
creation. This includes deep generative 3D-aware image synthesis, which produces high …

Previous animatable 3D-aware GANs for human generation have primarily focused on
either the human head or full body. However, head-only videos are relatively uncommon in …