用显式速度场直接变形隐式表面，无需中间监督。
Implicit Neural Surface Deformation with Explicit Velocity Fields
- 用显式速度场建模点运动，通过修正的等值面方程直接变形隐式场
- 在无中间形状监督下，同时处理刚性与非刚性变形，保持体积守恒
- 方法物理合理，重建质量与效率均优于现有技术
本文提出首个无监督方法，可同时预测时变神经隐式表面及点云对之间的形变。我们采用显式速度场建模点运动，并通过改进的水平集方程直接变形时变隐式场。该方程以紧凑形式结合等距约束下的等值面演化，确保符号距离场完整性。通过对速度场施加平滑且体积守恒的约束，方法成功恢复物理合理的中间形态。实验表明，该方法在无需中间形状监督的情况下，能有效处理刚性和非刚性形变，在质量和效率上显著优于现有方法。
原文摘要 · Abstract (English)
In this work, we introduce the first unsupervised method that simultaneously predicts time-varying neural implicit surfaces and deformations between pairs of point clouds. We propose to model the point movement using an explicit velocity field and directly deform a time-varying implicit field using the modified level-set equation. This equation utilizes an iso-surface evolution with Eikonal constraints in a compact formulation, ensuring the integrity of the signed distance field. By applying a smooth, volume-preserving constraint to the velocity field, our method successfully recovers physically plausible intermediate shapes. Our method is able to handle both rigid and non-rigid deformations without any intermediate shape supervision. Our experimental results demonstrate that our method significantly outperforms existing works, delivering superior results in both quality and efficiency.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。