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从单一图像中重建复杂形状的服装,具有特征稳定的未签名距离场.

Xinqi Liu, Jituo Li, Guodong Lu

    IEEE transactions on visualization and computer graphics
    |March 26, 2024
    PubMed
    概括

    这项研究引入了一种用于单图像服装重建的新方法,产生多样化和复杂的服装形状. 该方法使用隐式无符号距离字段和双阶段网格提取来获得详细和可编辑的服装模型.

    科学领域:

    • 计算机视觉 计算机视觉
    • 计算机图形 计算机图形
    • 三维重建的3D重建

    背景情况:

    • 传统的单视图服装重建方法使用固定的模板,限制形状多样性和轮复杂性.
    • 现有的方法难以处理姿势变化和遮,导致简化或不完整的重建.

    研究的目的:

    • 从单一图像中开发一种用于重建复杂服装形状轮和开放服装网格的新方法.
    • 为了提高姿势的坚固性,并产生各种各样的服装形状,超越固定模板的限制.

    主要方法:

    • 利用基于面向服装和姿势稳定的空间特征的隐式未签名距离场.
    • 采用一种类型通用服装模板,该模板来自主流的生成模型.
    • 通过点云表示实现两阶段服装网格提取方法,以获得平滑和可编辑的输出.

    主要成果:

    • 提出的方法成功地从单个图像中生成复杂的形状轮和开放的服装网格.
    • 在广泛的实验中实现了最先进的性能,证明了卓越的结果.
    • 这种方法提供了空间对齐的服装形状,增强了姿势的强度.

    结论:

    • 这种新的方法提供了一个简单,有效和低成本的解决方案,用于从单个图像中重建复杂的服装形状.

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  • 该技术克服了固定模板的局限性,使重建服装具有更大的多样性和细节.
  • 开发的数据集通过增加姿势多样性和解决遮问题来加强监督.