Ieee Transactions on Visualization and Computer Graphics 1 Efficient and Flexible Sampling with Blue Noise Properties of Triangular Meshes

By Massimiliano Corsini, Paolo Cignoni, Roberto Scopigno

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Yifan Wang
2. Daniel Cohen-Or
3. Ruihui Li
4. Chi-Wing Fu
5. Shihao Wu
6. Kang Yin
7. Olga Sorkine-Hornung
8. P. Heng

Citations in the corpus

• Learning Implicit Fields for Generative Shape Modeling (2018, methodology): “To compare with other methods that output point clouds, we first used Marching Cubes to obtain meshes from the 2563- voxelized models, then used Poisson-disk Sampling [10] to obtain 10000 points.”
• SUM: A Benchmark Dataset of Semantic Urban Meshes (2021, methodology): “We use Montecarlo sampling [44] to generate randomly uniform dense samples, and we further prune these samples according to Poisson distributions [45] and assign the colour via searching the nearest neighbour from the textures.”
• PU-GAN: A Point Cloud Upsampling Adversarial Network (2019, methodology): “On each patch, we further use Poisson disk sampling [5] to generate Q̂, which is a target point set of rN points on the patch.”
• Patch-Based Progressive 3D Point Set Upsampling (2018, methodology): “We use the Poisson-disk sampling [7] implemented in Meshlab [6] to sample input and ground truth point sets with the number of points ranging from 625 to 80000.”
• P2P-NET: Bidirectional Point Displacement Net for Shape Transform (methodology): “Given a set of 3D shapes, we convert them to surface samples with Poisson disk sampling [Corsini et al. 2012].”
• Differentiable surface splatting for point-based geometry processing (2019, methodology): “We use Poisson-disk sampling [Corsini et al. 2012] implemented in Meshlab [Cignoni et al. 2008] to sample 20K points per model as reference points, and create noisy input points by adding white Gaussian noise, then we compute the PCA normal [Hoppe et al. 1992] for both the reference and input…”