Inverse Procedural Appearance Design

Anno
2021
Proponente Marzia Riso - Dottorando
Sottosettore ERC del proponente del progetto
PE6_8
Componenti gruppo di ricerca
Componente Categoria
Fabio Pellacini Aggiungi Tutor di riferimento (Professore o Ricercatore afferente allo stesso Dipartimento del Proponente)
Abstract

The creation of realistic content and materials plays a central role in both the videogame and movie industries. Even though in the last few years hardware components and software greatly improved the design of realistic assets, this aspect is still a bottleneck in terms of control capabilities and ease of use.

Designing a realistic material means identifying a set of physical parameters that define the behaviour of light at each point location, which is described by functions called Bidirectional Scattering Distribution Function (BSDFs).

Many methodologies are used in material design, such as 3D material scanning or material synthesis with Generative Adversarial Networks (GANs). However, each technique did not allow artists to edit these materials in an easy way. Materials could also be generated using procedural programs. These are programs that map a data-flow graph of consecutive operations controlled by a set of procedural parameters. This means that physical parameters are not directly manipulated by artists, but are generally computed by a program given some high-level parameters. So, designing a specific and realistic material is challenging even for experienced artists.

We aim to build an Inverse Procedural Appearance Design framework to facilitate the usage of procedural programs. Given an image that represents the desired appearance, we aim to identify the procedural parameters that minimize the distance between the output of the procedural program and the image itself.
Once a first estimation of the procedural parameters is computed, artists can modify them to obtain slightly different results that better match the desired appearance, thus reducing the time consumed and allowing an easier interaction and control.

ERC
PE6_8, PE6_11
Keywords:
COMPUTER GRAPHICS, COMPUTER VISION, APPRENDIMENTO AUTOMATICO, INTELLIGENZA ARTIFICIALE

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