基于2D对应引导的3D形状匹配框架，提升复杂情况下的稳定性。
Stable-SCore: A Stable Registration-based Framework for 3D Shape Correspondence
- 用2D对应关系指导3D网格变形，增强匹配稳定性。
- 在非等距形变等挑战场景下性能显著优于现有方法。
- 适合需要高鲁棒性3D对应的应用，如角色重拓扑、属性迁移。
建立角色形状对应是计算机视觉与图形学中的关键基础任务，广泛应用于重拓扑、属性迁移和形状插值。现有主流函数映射方法在控制环境下有效，但在真实场景中面对非等距形变等复杂挑战时表现不佳。为此，我们重新审视基于配准的对应方法，挖掘其在更稳定形状对应估计方面的潜力。为克服其常见问题——如变形不稳定、需精细预对齐或高质量初始3D对应，我们提出Stable-SCore：一种基于配准的3D形状对应稳定框架。首先，复用一个可靠的2D角色对应基础模型以确保稳定的2D映射；关键地，我们提出一种新型语义流引导配准方法，利用2D对应引导网格变形。实验表明，该框架在挑战性场景中显著超越现有方法，为诸多实际应用带来新可能。
原文摘要 · Abstract (English)
Establishing character shape correspondence is a critical and fundamental task in computer vision and graphics, with diverse applications including re-topology, attribute transfer, and shape interpolation. Current dominant functional map methods, while effective in controlled scenarios, struggle in real situations with more complex challenges such as non-isometric shape discrepancies. In response, we revisit registration-for-correspondence methods and tap their potential for more stable shape correspondence estimation. To overcome their common issues including unstable deformations and the necessity for careful pre-alignment or high-quality initial 3D correspondences, we introduce Stable-SCore: A Stable Registration-based Framework for 3D Shape Correspondence. We first re-purpose a foundation model for 2D character correspondence that ensures reliable and stable 2D mappings. Crucially, we propose a novel Semantic Flow Guided Registration approach that leverages 2D correspondence to guide mesh deformations. Our framework significantly surpasses existing methods in challenging scenarios, and brings possibilities for a wide array of real applications, as demonstrated in our results.
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