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

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
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article

Make-A-Texture: Fast Shape-Aware Texture Generation in 3 Seconds

Ita Lifshitz, Omri Armstrong, Xiaoyu Xiang, Forrest Iandola et al.
2 citations
Computer Graphics and Visualization Techniques
7.08
article

Make-A-Texture: Fast Shape-Aware Texture Generation in 3 Seconds

Ita Lifshitz, Omri Armstrong, Xiaoyu Xiang, Forrest Iandola, Rakesh Ranjan, Yuchen Fan, Yilei Li, Liat Sless Gorelik
article en
2 citations

Abstract

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.

Openalex Percentile: Top 4%
Computer Graphics and Visualization Techniques
7.08
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Make-A-Texture: Fast Shape-Aware Texture Generation in 3 Seconds — Ita Lifshitz, Omri Armstrong, et al. · (2025) | TGRS Research Map | TGRS