用神经壳纹理分离几何与外观，减少模型所需点数。
Neural Shell Texture Splatting: More Details and Fewer Primitives
- 用全局神经壳纹理解耦表面纹理与几何表示
- 仅用少量高斯点即可还原精细纹理细节
- 适合追求参数效率的3D重建与网格提取场景
高斯点阵在新视角合成中表现优异，但需大量点以维持高质量。我们发现这是由于几何与外观信息纠缠所致。为此，提出神经壳纹理，作为表面周围纹理的全局表示。将高斯点同时用于几何建模和纹理采样，在图像空间高效投射纹理特征。实验表明，该解耦策略实现高参数效率、精细纹理重建，并可轻松生成带纹理的网格，同时使用显著更少的点数。
原文摘要 · Abstract (English)
Gaussian splatting techniques have shown promising results in novel view synthesis, achieving high fidelity and efficiency. However, their high reconstruction quality comes at the cost of requiring a large number of primitives. We identify this issue as stemming from the entanglement of geometry and appearance in Gaussian Splatting. To address this, we introduce a neural shell texture, a global representation that encodes texture information around the surface. We use Gaussian primitives as both a geometric representation and texture field samplers, efficiently splatting texture features into image space. Our evaluation demonstrates that this disentanglement enables high parameter efficiency, fine texture detail reconstruction, and easy textured mesh extraction, all while using significantly fewer primitives.
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