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微梦者:通过基于分数的代重建,在$\sim$20秒内高效的3D生成

Luxi Chen, Zhengyi Wang, Zihan Zhou

    IEEE transactions on pattern analysis and machine intelligence
    |August 19, 2025
    PubMed
    概括

    MicroDreamer通过引入基于分数的代重建 (SIR) 来增强零拍摄的3D生成,显著减少功能评估,并优化像素空间以获得更快的结果. 这种高效的算法实现了与现有方法可比的性能,同时在神经辐射场和网格生成方面速度快5-20倍.

    科学领域:

    • 计算机视觉 计算机视觉
    • 3D 计算机图形 3D 计算机图形
    • 机器学习 机器学习

    背景情况:

    • 基于优化的方法,如分数蒸采样 (SDS),对零射击3D生成有希望,但由于高函数评估和潜在空间限制,它们效率低下.
    • 现有的方法在3D重建任务中难以平衡生成速度和质量.

    研究的目的:

    • 引入一个高效和通用的算法,基于分数的代重建 (SIR),用于3D生成.
    • 为了实现像素空间的优化,并减少与传统SDS方法相比的函数评估 (NFEs) 的数量.
    • 介绍一下MicroDreamer,它是各种3D表示和生成任务的高效方法.

    主要方法:

    • 开发了基于分数的代重建 (SIR),一种模仿可微分3D重建的算法.
    • 在像素空间中实现了代优化,与SDS的单步隐藏空间优化形成鲜明对比.
    • 集成SIR与基于多视图分数的扩散模型以及优化训练以提高性能.

    主要成果:

    • 微梦者显示了5-20倍的速度改进比SDS神经辐射场生成与可比质量的神经辐射场的质量.
    • 在单一的A100 GPU上,通过3D高斯斯喷在约20秒内实现了网格生成.
    • 超过了基线DreamGaussian的显著差距,同时将生成时间减半.

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    结论:

    • 在高效和高质量的零拍摄3D生成中,MicroDreamer提供了实质性的进步.
    • 该SIR算法提供了适用于各种3D表示和任务的通用和有效框架.
    • 这项工作大大降低了3D内容创建的计算成本和时间.