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cs.GR2026
SAND: Spatially Adaptive Network Depth for Fast Sampling of Neural Implicit Surfaces
Chuanxiang Yang, Junhui Hou, Yuan Liu +5
Implicit neural representations are powerful for geometric modeling, but their practical use is often limited by the high computational cost of network evaluations. We observe that…
cs.GR2026
Filmsticking++: Rapid Film Sticking for Explicit Surface Reconstruction
Pengfei Wang, Jian Liu, Qiujie Dong +5
Explicit surface reconstruction aims to generate a surface mesh that exactly interpolates a given point cloud. This requirement is crucial when the point cloud must lie non-negotia…
cs.GR2025
NeuVAS: Neural Implicit Surfaces for Variational Shape Modeling
Pengfei Wang, Qiujie Dong, Fangtian Liang +11
Neural implicit shape representation has drawn significant attention in recent years due to its smoothness, differentiability, and topological flexibility. However, directly modeli…