MesoGAN: Generative Neural Reflectance Shells

Stavros Diolatzis, Jan Novák, Fabrice Rousselle, Jonathan Granskog, Miika Aittala, Ravi Ramamoorthi, George Drettakis

Computer Graphics Forum (presented at EGSR 2023), vol. 42, no. 6

Our method combines the strengths of StyleGAN and volumetric neural field rendering to generate a 3D mesoscale texture that can be mapped to objects and used in a path tracer (c). We train on datasets of synthetic patches (a); our method can generate textures that have artistic parameters (such as fur saturation and length) which can be used to create shell maps of arbitrary extent (b).

abstract

We introduce MesoGAN, a model for generative 3D neural textures. This new graphics primitive represents mesoscale appearance by combining the strengths of generative adversarial networks (StyleGAN) and volumetric neural field rendering. The primitive can be applied to surfaces as a neural reflectance shell; a thin volumetric layer above the surface with appearance parameters defined by a neural network. To construct the neural shell, we first generate a 2D feature texture using StyleGAN with carefully randomized Fourier features to support arbitrarily sized textures without repeating artefacts. We augment the 2D feature texture with a learned height feature, which aids the neural field renderer in producing volumetric parameters from the 2D texture. To facilitate filtering, and to enable end-to-end training within memory constraints of current hardware, we utilize a hierarchical texturing approach and train our model on multi-scale synthetic datasets of 3D mesoscale structures. We propose one possible approach for conditioning MesoGAN on artistic parameters (e.g. fibre length, density of strands, lighting direction) and demonstrate and discuss integration into physically based renderers.

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bibtex

@article{diolatzis2023mesogan,
    author = {Diolatzis, Stavros and Nov\'{a}k, Jan and Rousselle, Fabrice and Granskog, Jonathan and Aittala, Miika and Ramamoorthi, Ravi and Drettakis, George},
    title = {MesoGAN: Generative Neural Reflectance Shells},
    journal = {Computer Graphics Forum},
    year = {2023},
    month = {Sep}
    volume = {42},
    number = {6},
    keywords = {rendering, ray tracing, rendering, global illumination, rendering, reflectance and shading models},
    doi = {https://doi.org/10.1111/cgf.14846},
    url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14846},
}