Winners
The Computer Graphics Forum 2019 Cover Image has been selected by the CGF editorial board. We thanks all people who submitted this year, and hope that they will participate to the next year contest.
Winner of the Computer Graphics Forum 2019 Cover Image Contest
Kai Lawonn (1) and Tobias Günther (2)
(1) University of Koblenz-Landau
(2) ETH Zürich
This image shows a triangulation of three ballet dancers at sunset. This stylization was obtained with our interactive and user-centered image triangulation algorithm, which is based on an interactive optimization that places triangles with constant color or linear color gradients to fit a target image. The efficient GPU implementation is described in the paper 'Stylized Image Triangulation' by Lawonn and Günther, DOI: 10.1111/cgf.13526.
Second place:
Gilles Rainer (1), Wenzel Jakob (2), Abhijeet Ghosh (3) and Tim Weyrich (1)
(1) University College London
(2) EPFL
(3) Imperial College London
The image shows a physically-based rendering of a piece of fabric draped over a glass sphere, produced through pathtracing in Mitsuba. The scene geometry was created in Blender via a physical simulation of the cloth falling onto rigid objects. The appearance of the silk was rendered with a new plugin based on a compressed representation of Bidirectional Texture Functions using neural networks, from our unpublished work that is currently under review. The fabric material exhibits complex spatial variation and specularities as well as strong anisotropy that our compressed neural material descriptor manages to accurately reproduce. The glass sphere reflects some of the environment as well as some close ups of the textile.
Third place:
Adrian Jarabo (1), Carlos Aliaga (2) and Diego Gutierrez (1)
(1) Universidad de Zaragoza, I3A
(2) Desilico Labs
The image shows a render of an iceberg made of compacted snow, where the snow scatterers have positive correlation, and therefore the iceberg shows super-exponential power-law-based transmittance, following our radiative model for correlated participating media.
Our model extends classic uncorrelated radiative transfer equation, accounting for non-exponential probability of extinction arising from scatterers spatial correlation. It accounts for multiple sources of correlation, boundary conditions, and mixtures of scatterers.
Our model and further details can be found in "A Radiative Transfer Framework for Spatially-Correlated Materials", ACM Trans. Graphics, Vol. 37(4), 2018.