Volumetric Surfaces: Representing Fuzzy Geometries with Layered Meshes

Stefano Esposito, Anpei Chen, Christian Reiser, Samuel Rota Bulò, Lorenzo Porzi, Katja Schwarz, Christian Richardt, Michael Zollhöfer, Peter Kontschieder, Andreas Geiger; Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR), 2025, pp. 21370-21380

High-quality view synthesis relies on volume rendering, splatting, or surface rendering. While surface rendering is typically the fastest, it struggles to accurately model fuzzy geometry like hair. In turn, alpha-blending techniques excel at representing fuzzy materials but require an unbounded number of samples per ray (P1). Further overheads are induced by empty space skipping in volume rendering (P2) and sorting input primitives in splatting (P3). We present a novel representation for real-time view synthesis where the (P1) number of sampling locations is small and bounded, (P2) sampling locations are efficiently found via rasterization, and (P3) rendering is sorting-free. We achieve this by representing objects as semi-transparent multi-layer meshes rendered in a fixed order. First, we model surface layers as signed distance function (SDF) shells with optimal spacing learned during training. Then, we bake them as meshes and fit UV textures. Unlike single-surface methods, our multi-layer representation effectively models fuzzy objects. In contrast to volume and splatting-based methods, our approach enables real-time rendering on low-power laptops and smartphones.