Generating Digital Models Using Text-to-3D and Image-to-3D Prompts: Critical Case Study

TL;DR

This paper critically examines online text-to-3D and image-to-3D generative tools, analyzing their effectiveness in producing high-quality digital models to enhance automation in 3D creation.

Contribution

It provides a comprehensive review and critical analysis of current AI-based 3D model generators, highlighting their strengths and limitations.

Findings

Some tools produce high-quality models with specific prompts.

Variability in output quality across different generators.

Identifies key challenges in automated 3D model generation.

Abstract

In the world of technology and AI, digital models play an important role in our lives and are an essential part of the digital twins of real-world objects. They can be created by designers, artists, or game developers using spline curves and surfaces, meshes, and voxels, but making such models is too time-consuming. With the growth of AI tools, there is interest in the automated generation of 3D models, such as generative design approaches, which can save creators valuable time. This paper reviews several online 3D model generators and critically analyses the results, hoping to see higher-quality results from different prompts.