Spaghetti Splatting Fixes 3D AI's Biggest Blind Spot on Hair and Wires

Takeaways

• Spaghetti Splatting generalizes 3D Gaussian Splatting by replacing point primitives with polyline curves convolved with Gaussian or Beta kernels.
• A zero-length spaghetti equals a Gaussian splat, making the representation a strict superset of 3DGS.
• Per-segment camera linearization enables closed-form rendering and fast training with non-Gaussian kernels.
• Outperforms specialized line methods and Gaussian Haircut on hair datasets while staying competitive on Mip-NeRF 360.
• Produces connected strands directly usable in physics simulation, with native anti-aliasing from the convolution formulation.
• Paper and project page available at spaghetti-splatting.github.io ; code not yet released.