Signing the Unsigned: Robust Surface Reconstruction from Raw Pointsets
By Patrick Mullen, F. Goes, Mathieu Desbrun, David Cohen-Steiner, Pierre Alliez. 2010
150 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- Yaron Lipman
- M. Ovsjanikov
- Matan Atzmon
- Niloy J. Mitra
- Paul Guerrero
- Hugues Hoppe
- M. Kazhdan
- Yanir Kleiman
In Computer Graphics and Computer-Aided Design
- Yaron Lipman
- M. Ovsjanikov
- Matan Atzmon
- Niloy J. Mitra
- Hugues Hoppe
- M. Kazhdan
- Paul Guerrero
- Yanir Kleiman
Citations in the corpus
- PCPNet Learning Local Shape Properties from Raw Point Clouds (2017, background): “As a result, they have has been extended significantly in recent years both through more robust estimates [HLZ ∗ 09] and global techniques based on signed distance computations [MDGD ∗ 10], among others.”
- Screened poisson surface reconstruction (2013, background): “If the input points are unoriented, an important step is to correctly infer the sign of the resulting distance .eld [Mullen et al. 2010].”
- A Survey of Surface Reconstruction from Point Clouds (2017, unknown): “[KBH06] general implicitfield GraphCut[HK06] general volumetricsegmentation UnorientedIndicator[ACSTD07] general implicitfield LOP[LCOLTE07] general pointset DictionaryLearning[XZZ ∗ 14] general mesh Visibility VRIP[CL96] general implicitfield TVL1-VRIP[ZPB07] general implicitfield SigningtheUnsigned[MD”
- SAL: Sign Agnostic Learning of Shapes From Raw Data (2019, background): “[29] suggests to sign an unsigned distance function to a point cloud by a multistage algorithm first dividing the problem to near and far”