Existing methods for 3D-aware image synthesis largely depend on the 3D pose distribution
pre-estimated on the training set. An inaccurate estimation may mislead the model into …

This review thoroughly examines the role of semantically-aware Neural Radiance Fields
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …

Generative adversarial networks (GANs), a novel framework for training generative models
in an adversarial setup, have attracted significant attention in recent years. The two …

We introduce VIVE3D, a novel approach that extends the capabilities of image-based 3D
GANs to video editing and is able to represent the input video in an identity-preserving and …

Generating 3D models lies at the core of computer graphics and has been the focus of
decades of research. With the emergence of advanced neural representations and …

Generating 3D models lies at the core of computer graphics and has been the focus of
decades of research. With the emergence of advanced neural representations and …

Existing text-based 3D generation methods generate attractive results but lack detailed
geometry control. Sketches, known for their conciseness and expressiveness, have …

This work presents 3DPE, a practical tool that can efficiently edit a face image following
given prompts, like reference images or text descriptions, in the 3D-aware manner. To this …

Existing 3D-aware portrait synthesis methods can generate impressive high-quality images
while preserving strong 3D consistency. However, most of them cannot support the fine …

To address the problem of incomplete perception of limited viewpoints of ore blocks in future
remote and intelligent shoveling-dominated mining scenarios, a method of using new view …