# Neural Denoising for Deep-Z Monte Carlo Renderings

Supplementary Material – Eurographics 2024

Xianyao Zhang, Gerhard Röthlin, Shilin Zhu, Tunç Ozan Aydın, Farnood Salehi, Markus Gross, Marios Papas

ETH Zürich, Disney Research | Studios, and Pixar Animation Studios

## Comparison with Vicini19 and flat denoiser – Test Set

Comparing the proposed deep-Z denoiser with the non-neural Vicini19 deep-Z denoiser and a multi-scale kernel-predicting flat denoiser.

Scene A
Scene B
Scene C
Scene D
Scene E
Scene F
Scene G
Scene H
Scene I
Scene J

## Comparison with and without hybrid flat–deep-Z architecture – Test Set

Comparing the proposed deep-Z denoiser with the deep-Z-only variant, which only has the deep reconstruction heads, and does not receive pixel context at the input.

Scene A
Scene B
Scene C
Scene D
Scene E
Scene F
Scene G
Scene H
Scene I
Scene J

## Comparison with and without depth-aware operators – Test Set

Comparing the proposed deep-Z denoiser with the non-depth-aware variant.

Scene A
Scene B
Scene C
Scene D
Scene E
Scene F
Scene G
Scene H
Scene I
Scene J

Images are © Disney.