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English(EN) ETCH-X: Robustify Expressive Body Fitting to Clothed Humans with Composable Datasets

ETCH-X 和 OmniFit 通过新方法推进带衣三维人体拟合

研究人员开发了 ETCH-X,一种将参数化人体模型拟合到带衣人体三维扫描的先进方法。这种新方法通过引入“贴合度感知”拟合范式来处理服装动力学,并利用 SMPL-X 扩展表达性,从而改进了其前身。ETCH-X 利用隐式密集对应而非显式标记来实现更高的鲁棒性和精细的细节,在各种数据集上取得了显著的性能提升。 AI

影响 三维人体拟合的进步可以改进动画和纹理化等下游任务,可能对虚拟现实和数字内容创作产生影响。

排序理由 该集群包含两篇 arXiv 论文,详细介绍了三维人体拟合的新方法。

在 arXiv cs.CV 阅读 →

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ETCH-X 和 OmniFit 通过新方法推进带衣三维人体拟合

报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Xiaoben Li, Jingyi Wu, Zeyu Cai, Siyuan Yu, Boqian Li, Yuliang Xiu ·

    ETCH-X: Robustify Expressive Body Fitting to Clothed Humans with Composable Datasets

    arXiv:2604.08548v3 Announce Type: replace Abstract: Human body fitting, which aligns parametric body models such as SMPL to raw 3D point clouds of clothed humans, serves as a crucial first step for downstream tasks like animation and texturing. An effective fitting method should …

  2. arXiv cs.CV TIER_1 English(EN) · Zhenyu Zhang ·

    OmniFit: Multi-modal 3D Body Fitting via Scale-agnostic Dense Landmark Prediction

    Fitting an underlying body model to 3D clothed human assets has been extensively studied, yet most approaches focus on either single-modal inputs such as point clouds or multi-view images alone, often requiring a known metric scale. This constraint is frequently impractical, espe…