… Figure 1 Figure 1: We present a neural latent representation for BRDFs and a BRDF layering
network based on it. Our method is able to produce closely matching layered results to the …

… Before using our Neural BRDF models for rendering, we do some preparation: for rough
conductor/dielectric BRDFs and the components of layered BRDFs, we represent them by the …

… neural rendering-based method called NeRO for reconstructing the geometry and the BRDF
… Recent neural rendering techniques can model the interaction between environment lights …

… material layering in the neural space with the latent code compressed by a neural network.
… Our goal is to represent bidirectional reflectance distribution function (BRDF) using a neural …

… models for the real-world and semi-synthetic data originates from the number of layers (NOL)
for the directions, we perform experiments where we vary this parameter for each of the …

… BRDF-NeRF, which incorporates the physically-based semi-empirical Rahman–Pinty–Verstraete
(RPV) BRDF … Our BRDF-NeRF successfully synthesises novel views from unseen …

… learn a neural 3D volume V where, at each point x ∈ R3, we estimate the BRDF parameters
… -PIL takes ωr as input, and we condition the first few layers of the network with illumination zl…

… In opposition to an empirical BRDF, in this work we chose a … based on neural networks to
automatically estimate the BRDF pa… layered in a stack of multiple BSDFs, for the purpose of this …

… In effect, the autoencoder learns to predict the weights of an NBRDF neural network. We
typically use NBRDF encodings with two hidden layers urn:x-wiley:01677055:media:cgf14335:…

… In this work, we represent the BRDF function through neural networks implicitly instead of …
) layers. The aggregator network a starts with mean operation, followed by additional FC layers …