In this work, we present a novel framework built to simplify 3D asset generation for amateur
users. To enable interactive generation, our method supports a variety of input modalities …

Although the recent rapid evolution of 3D generative neural networks greatly improves 3D
shape generation, it is still not convenient for ordinary users to create 3D shapes and control …

In the rapidly advancing field of multi-modal machine learning (MMML), the convergence of
multiple data modalities has the potential to reshape various applications. This paper …

Text-to-3D generation has shown rapid progress in recent days with the advent of score
distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural …

Abstract We present Text2Tex, a novel method for generating high-quality textures for 3D
meshes from the given text prompts. Our method incorporates inpainting into a pre-trained …

We propose SceneTex a novel method for effectively generating high-quality and style-
consistent textures for indoor scenes using depth-to-image diffusion priors. Unlike previous …

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

Abstract 3D shape modeling is labor-intensive, time-consuming, and requires years of
expertise. To facilitate 3D shape modeling, we propose a 3D shape generation network that …

This paper presents a new approach for 3D shape generation, inversion, and manipulation,
through a direct generative modeling on a continuous implicit representation in wavelet …

Generating faithful visualizations of human faces requires capturing both coarse and fine-
level details of the face geometry and appearance. Existing methods are either data-driven …