Sphere Carving: Bounding Volumes for Signed Distance Fields
Hugo Schott, Theo Thonat, Thibaud Lambert, Eric Guérin, Eric Galin, Axel Paris
Abstract
We introduce Sphere Carving , a novel method for automatically computing bounding volumes that closely bound a procedurally defined implicit surface. Starting from an initial bounding volume located far from the object, we iteratively approach the surface by leveraging the signed distance function information. Field function queries define a set of empty spheres, from which we extract intersection points that are used to compute a bounding volume. Our method is agnostic of the function representation and only requires a conservative signed distance field as input. This encompasses a large set of procedurally defined implicit surface models such as exact or Lipschitz functions, BlobTrees, or even neural representations. Sphere Carving is conceptually simple, independent of the function representation, requires a small number of function queries to create bounding volumes, and accelerates queries in Sphere Tracing and polygonization.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 5d225a2e-c817-4838-bed1-69753d87da84Cited by top-tier papers1
Ask how each one uses itBuilds on5
- Spelunking the deep: guaranteed queries on general neural implicit surfaces via range analysisNicholas Sharp, Alec JacobsonSIGGRAPH 2022 · 45 citations
- Massively parallel rendering of complex closed-form implicit surfacesMatthew KeeterSIGGRAPH 2020 · 29 citations
- Reach for the Arcs: Reconstructing Surfaces from SDFs via Tangent PointsSilvia Sellán, Yingying Ren, Christopher Batty, Oded SteinSIGGRAPH 2024 · 10 citations
- Neural BoundingStephanie Wenxin Liu, Michael Fischer, Paul D. Yoo, Tobias RitschelSIGGRAPH 2024 · 3 citations
- Neural Geometric Level of Detail: Real-Time Rendering With Implicit 3D ShapesTowaki Takikawa, Joey Litalien, Kangxue Yin, Karsten Kreis et al.CVPR 2021
Related papers
- Ray Tracing Harmonic FunctionsMark Gillespie, Denise Yang, Mario Botsch, Keenan CraneSIGGRAPH 2024 · 10 citations
- Points as Tori: Fast Pointwise Signed Distance for Point CloudsNicole Feng, Ioannis Gkioulekas, Keenan CraneSIGGRAPH 2026 · 1 citation
- Deep Implicit Surface Point Prediction NetworksRahul Venkatesh, Tejan Karmali, Sarthak Sharma, Aurobrata Ghosh et al.ICCV 2021 · 57 citations
- DIST: Rendering Deep Implicit Signed Distance Function With Differentiable Sphere TracingShaohui Liu, Yinda Zhang, Songyou Peng, Boxin Shi et al.CVPR 2020
- Marching-Primitives: Shape Abstraction from Signed Distance FunctionWeixiao Liu, Yuwei Wu, Sipu Ruan, Gregory S. ChirikjianCVPR 2023
