Make-A-Texture：3秒内快速生成形状感知纹理
Make-A-Texture: Fast Shape-Aware Texture Generation in 3 Seconds
AI总结：
提出Make-A-Texture框架，利用深度感知扩散模型和自动视角选择算法，在3.07秒内为3D几何体生成高质量多视角一致纹理，显著提升3D内容创作效率。
摘要：
我们提出了Make-A-Texture，一个新框架，能根据文本提示为给定的3D几何体高效合成高分辨率纹理贴图。我们的方法利用深度感知修复扩散模型，在由自动视角选择算法确定的优化视角序列中，逐步生成多视角一致的纹理。该方法的一个显著特点是其卓越的效率，在单块NVIDIA H100 GPU上仅需3.07秒的端到端运行时间即可完成完整纹理生成，显著优于现有方法。这种加速是通过优化扩散模型和专用反投影方法实现的。此外，通过选择性地遮蔽非正面面及开放曲面物体的内部面，我们的方法减少了反投影阶段的伪影。实验结果表明，Make-A-Texture匹配或超越了其他最先进方法的质量。我们的工作显著提升了纹理生成模型在真实世界3D内容创作中的适用性和实用性，包括交互式创作和文本引导的纹理编辑。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
