用三角形片与软连接力优化3D场景，提升重建精度。
Radiant Triangle Soup with Soft Connectivity Forces for 3D Reconstruction and Novel View Synthesis
- 以离散透明三角形片为几何外观表示，支持灵活组合
- 引入软连接力使三角形间保持平滑连续，提升几何准确性
- 适合需要高精度3D重建的视觉任务，如新视角合成
我们提出一种推理时场景优化算法，采用三角形片（triangle soup）作为场景几何与外观的表示，即一组不连通的透明三角形基元。相比全秩高斯核，三角形是局部平坦的自然表面代理，可组合实现复杂几何结构。结合顶点级球谐函数（Spherical Harmonics, SH），在不显著增加基元数量的前提下提供丰富的视觉表现。我们通过直接在基元上施加优化目标和空间正则化，提升重建质量。方法核心在于优化过程中定义并施加三角形间的软连接力，实现显式的但柔性的表面连续性。在典型3D重建与新视角合成数据集上的实验表明，该方法在不牺牲视觉保真度的前提下，相比现有最先进算法提升了几何精度。
原文摘要 · Abstract (English)
We introduce an inference-time scene optimization algorithm utilizing triangle soup, a collection of disconnected translucent triangle primitives, as the representation for the geometry and appearance of a scene. Unlike full-rank Gaussian kernels, triangles are a natural, locally-flat proxy for surfaces that can be connected to achieve highly complex geometry. When coupled with per-vertex Spherical Harmonics (SH), triangles provide a rich visual representation without incurring an expensive increase in primitives. We leverage our new representation to incorporate optimization objectives and enforce spatial regularization directly on the underlying primitives. The main differentiator of our approach is the definition and enforcement of soft connectivity forces between triangles during optimization, encouraging explicit, but soft, surface continuity in 3D. Experiments on representative 3D reconstruction and novel view synthesis datasets show improvements in geometric accuracy compared to current state-of-the-art algorithms without sacrificing visual fidelity.
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