A Survey of Procedural Noise Functions

By Ares Lagae, Sylvain Lefebvre, Robert L. Cook, Tony DeRose, George Drettakis, David S. Ebert, John P. Lewis, Ken Perlin, Matthias Zwicker. 2010

220 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

1. Luis Muñoz-González
2. Marco Hutter
3. Vladlen Koltun
4. Emil C. Lupu
5. Philip H. S. Torr
6. Iasonas Kokkinos
7. Alan L. Yuille
8. Siddhartha Chaudhuri

In Computer Graphics and Computer-Aided Design

1. Vladlen Koltun
2. Leonidas J. Guibas
3. Siddhartha Chaudhuri
4. Andreas Geiger

Citations in the corpus

• Learning quadrupedal locomotion over challenging terrain (2020, background): “• The Hills terrain is based on Perlin noise [49].”
• Learning Ground Traversability From Simulations (2017, unknown): “Each terrain is generated by summing multiple realizations of random 2D simplex noise [27] (a variant of Perlin noise [28] frequently adopted in the procedural generation literature [29]) with different periods.”
• Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks (2018, methodology): “where σ is the width of the Gaussian, λ and ω are the period and orientation of the Harmonic function [34].”