# Magic3D: High-Resolution Text-to-3D Content Creation

**Authors:** Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin  
**arXiv:** [2211.10440](https://arxiv.org/abs/2211.10440)  
**Date:** 2022-11-18  
**Summary page:** https://www.summarizepaper.com/en/paper/2211.10440v2/

## Key points

- Magic3D is a novel method for efficiently synthesizing high-quality 3D models from text prompts
- Utilizes a two-stage optimization framework to address limitations of previous techniques like DreamFusion
- First stage involves optimizing a coarse neural field representation and memory-efficient scene representation for quick generation of view-consistent geometry
- Second stage optimizes mesh representations with high-resolution diffusion priors and efficient differentiable rasterizer for high-frequency details in geometry and texture
- Generates high-quality 3D mesh models in just 40 minutes, twice as fast as DreamFusion, with higher resolution
- Preferred by 61.7% of raters due to improved speed and quality compared to existing methods
- Offers unprecedented control over the 3D synthesis process, making it accessible for novices and enhancing workflow for expert artists
- Opens up new possibilities for creative applications in industries such as gaming, entertainment, architecture, and robotics simulation

## Summary

Introducing Magic3D: A Novel Method for Efficiently Synthesizing High-Quality 3D Models from Text Prompts

In this paper, we present Magic3D - a revolutionary approach to generating highly detailed 3D models from text prompts in a fraction of the time compared to existing methods. Our method addresses the limitations of previous techniques such as DreamFusion by utilizing a two-stage optimization framework. The first stage involves optimizing a coarse neural field representation using multiple diffusion priors and a memory- and compute-efficient scene representation based on a hash grid. This allows us to quickly generate view-consistent geometry while accelerating the process. In the second stage, we optimize mesh representations with high-resolution diffusion priors (up to 512 × 512) and utilize an efficient differentiable rasterizer and camera close-ups to recover high-frequency details in geometry and texture. Compared to DreamFusion's reported average processing time of 1.5 hours, Magic3D can generate high-quality 3D mesh models in just 40 minutes - twice as fast while achieving higher resolution. User studies have shown that our approach is preferred by 61.7% of raters due to its improved speed and quality. Our method also offers unprecedented control over the 3D synthesis process by incorporating advancements from text-to-image editing applications. This not only makes 3D content creation more accessible for novices but also enhances the workflow for expert artists. With its ability to efficiently create detailed 3D models, Magic3D opens up new possibilities for creative applications across various industries such as gaming, entertainment, architecture, and robotics simulation.