Abstract 3D city generation is a desirable yet challenging task since humans are more
sensitive to structural distortions in urban environments. Additionally generating 3D cities is …

Toward infinite-scale 3D city synthesis, we propose a novel framework, InfiniCity, which
constructs and renders an unconstrainedly large and 3D-grounded environment from …

Controllable scene synthesis aims to create interactive environments for various industrial
use cases. Scene graphs provide a highly suitable interface to facilitate these applications …

Generating photorealistic images with controllable camera pose and scene contents is
essential for many applications including AR/VR and simulation. Despite the fact that rapid …

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 DiffuScene for indoor 3D scene synthesis based on a novel scene configuration
denoising diffusion model. It generates 3D instance properties stored in an unordered object …

We present a generative neural network that enables us to generate plausible 3D indoor
scenes in large quantities and varieties, easily and highly efficiently. Our key observation is …

3D indoor scenes are widely used in computer graphics, with applications ranging from
interior design to gaming to virtual and augmented reality. They also contain rich …

In this paper we propose a neural message passing approach to augment an input 3D
indoor scene with new objects matching their surroundings. Given an input, potentially …

As pretrained text-to-image diffusion models become increasingly powerful recent efforts
have been made to distill knowledge from these text-to-image pretrained models for …