Make-A-Texture: Fast Shape-Aware Texture Generation in 3 Seconds
We present Make-A-Texture, a new framework that efficiently synthesizes high-resolution texture maps from textual prompts for given 3D geometries. Our approach progressively generates textures that are consistent across multiple viewpoints with a depth-aware inpainting diffusion model, in an optimized sequence of viewpoints determined by an automatic view selection algorithm. A significant feature of our method is its remarkable efficiency, achieving a full texture generation within an end-to-end runtime of just 3.07 seconds on a single NVIDIA H100 GPU, significantly outperforming existing methods. Such an acceleration is achieved by optimizations in the diffusion model and a specialized backprojection method. Moreover, our method reduces the artifacts in the backprojection phase, by selectively masking out non-frontal faces, and internal faces of open-surfaced objects. Experimental results demonstrate that Make-A-Texture matches or exceeds the quality of other state-of-the-art methods. Our work significantly improves the applicability and practicality of texture generation models for real-world 3D content creation, including interactive creation and text-guided texture editing.
Authors
- Ita Lifshitz
- Omri Armstrong
- Xiaoyu Xiang (ORCID: https://orcid.org/0000-0002-5999-9133)
- Forrest Iandola
- Rakesh Ranjan (ORCID: https://orcid.org/0000-0003-0963-4512)
- Yuchen Fan (ORCID: https://orcid.org/0000-0002-6637-7711)
- Yilei Li (ORCID: https://orcid.org/0000-0003-1855-0919)
- Liat Sless Gorelik
Publication Details
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1109/wacv61041.2025.00477
- Citations
- 2
- Primary Topic
- Computer Graphics and Visualization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 7.08