Technical Papers
Noise and Texture
Tuesday, 7 August 3:45 PM - 5:35 PM | Los Angeles Convention Center, Room 408A
Session Chair: Wojciech Jarosz, Disney Research Zürich
Noise and Texture
Gabor Noise by Example
Gabor noise by example is a method of estimating the parameters of bandwidth-quantized Gabor noise, a procedural noise function that can generate noise with an arbitrary power spectrum from exemplar Gaussian textures, a class of textures that is completely characterized by their power spectrum.
Bruno Galerne
Université Paris Descartes
Ares Lagae
Katholieke Universiteit Leuven
Sylvain Lefebvre
Alice/INRIA
George Drettakis
REVES/INRIA Sophia-Antipolis
Diffusion Curve Textures for Resolution-Independent Texture Mapping
Introducing a vector representation called diffusion curve textures for mapping diffusion-curve images (DCI) onto arbitrary surfaces. Diffusion-curve textures provide an explicit representation from which the texture value at any point can be solved directly, while preserving the compactness and resolution independence of diffusion curves.
Xin Sun
Microsoft Research Asia
Guofu Xie
Chinese Academy of Sciences
Yue Dong
Microsoft Research Asia
Stephen Lin
Microsoft Research Asia
Weiwei Xu
Microsoft Research Asia
Wencheng Wang
Chinese Academy of Sciences
Xin Tong
Microsoft Research Asia
Baining Guo
Microsoft Research Asia
Structure-Aware Synthesis for Predictive Woven Fabric Appearance
A technique for generating high-quality, micron-resolution volumetric appearance models of woven fabrics with user-specified designs. First, a small exemplar database is created by scanning fabric samples with elementary weave structures. Output volumes can then be synthesized by copying data from the exemplars at each yarn crossing.
Shuang Zhao
Cornell University
Kavita Bala
Cornell University
Steve Marschner
Cornell University
Wenzel Jakob
Cornell University
Point Sampling With General Noise Spectrum
The key contribution of this paper is an algorithm for generating point samples that match user-defined noise spectrum, such as blue, green, pink, and magenta noise. The algorithm supports adaptive sampling and is accelerated on the GPU. The paper shows a variety of sample patterns generated using the algorithm and demonstrates suitable applications.
Yahan Zhou
University of Massachusetts Amherst
Haibin Huang
University of Massachusetts Amherst
Li-Yi Wei
The University of Hong Kong
Rui Wang
University of Massachusetts Amherst
Symmetry-Guided Texture Synthesis and Manipulation
This paper presents a framework for symmetry-guided texture synthesis and manipulation. Methods are provided to control the symmetries of a texture and to transfer symmetries from one texture to another.
Vladimir Kim
Princeton University
Yaron Lipman
Weizmann Institute of Science
Thomas Funkhouser
Princeton University