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

Abstract 3D-aware generative adversarial networks (GANs) synthesize high-fidelity and
multi-view-consistent facial images using only collections of single-view 2D imagery …

While recent advancements in vision-language models have had a transformative impact on
multi-modal comprehension, the extent to which these models possess the ability to …

Synthesis and reconstruction of 3D human head has gained increasing interests in
computer vision and computer graphics recently. Existing state-of-the-art 3D generative …

In recent years, neural implicit surface reconstruction has emerged as a popular paradigm
for multi-view 3D reconstruction. Unlike traditional multi-view stereo approaches, the neural …

Abstract Monocular 3D Semantic Scene Completion (SSC) has garnered significant
attention in recent years due to its potential to predict complex semantics and geometry …

In this work, we present SceneDreamer, an unconditional generative model for unbounded
3D scenes, which synthesizes large-scale 3D landscapes from random noise. Our …

We present OmniAvatar, a novel geometry-guided 3D head synthesis model trained from in-
the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D …

We present a method that reconstructs and animates a 3D head avatar from a single-view
portrait image. Existing methods either involve time-consuming optimization for a specific …

Existing one-shot 4D head synthesis methods usually learn from monocular videos with the
aid of 3DMM reconstruction yet the latter is evenly challenging which restricts them from …