先说结论。它和通用视觉自监督的关系在于：用内在 geodesic metric 预训练 3D 表征，强调拓扑/流形结构而非外在坐标或语义标签。 中高相关；详见方法、贡献和实验边界。
Figureure 12 · The overall pipeline of our 3D shape correspondence framework.Figure 12. The overall pipeline of our 3D shape correspondence framework.这张图概括 From Extrinsic to Intrinsic 的整体方法流程。阅读时先看模块之间传递的训练信号，再看作者如何把目标拆成可优化的子问题。Figureure 1 · The overview of PRISM, including an intrinsic geometry-aware foundatioFigure 1. The overview of PRISM, including an intrinsic geometry-aware foundation model and a geodesic-driven training objective composed of geodesic structure and prediction. Our PRISM effectively facilitates downstream tasks that focus on fine geometric details and high-level semantics.这张图概括 From Extrinsic to Intrinsic 的整体方法流程。阅读时先看模块之间传递的训练信号，再看作者如何把目标拆成可优化的子问题。
核心问题
它和通用视觉自监督的关系在于：用内在 geodesic metric 预训练 3D 表征，强调拓扑/流形结构而非外在坐标或语义标签。
方法拆解
用内在 geodesic metric 预训练 3D 表征，强调拓扑/流形结构而非外在坐标或语义标签
