The Environments of Dune: Prophecy through the Gaussian Splat

We describe a production‑proven workflow that converts deep renders from Dune: Prophecy into compact, photoreal Gaussian‑splat assets for real‑time scouting. A custom Houdini Digital Asset (HDA) assembles COLMAP‑compatible training data from 3 K deep images, then Jawset Postshot trains ∼16 M‑point splats in 3 h on a single RTX 4090. Creatives explored both day and night versions of the kilometer‑scale Imperial Palace set at 60–90 fps, this opened the possibility of digital scouting a full CG environment. The approach delivers the visual fidelity of offline shading while slashing preview latency to seconds and paves the way for using trained splats as final‑pixel backgrounds in compositing.

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Publication Details

Published
2025-07-24
DOI
https://doi.org/10.1145/3721239.3734124
Primary Topic
Marine and environmental studies
Type
article
Field-Weighted Citation Impact
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article

The Environments of Dune: Prophecy through the Gaussian Splat

Julien Hery
Marine and environmental studies
article

The Environments of Dune: Prophecy through the Gaussian Splat

Julien Hery
article en

Abstract

We describe a production‑proven workflow that converts deep renders from Dune: Prophecy into compact, photoreal Gaussian‑splat assets for real‑time scouting. A custom Houdini Digital Asset (HDA) assembles COLMAP‑compatible training data from 3 K deep images, then Jawset Postshot trains ∼16 M‑point splats in 3 h on a single RTX 4090. Creatives explored both day and night versions of the kilometer‑scale Imperial Palace set at 60–90 fps, this opened the possibility of digital scouting a full CG environment. The approach delivers the visual fidelity of offline shading while slashing preview latency to seconds and paves the way for using trained splats as final‑pixel backgrounds in compositing.

Rolls-Royce (Canada) (CA)
Openalex Percentile: Top 81%
Marine and environmental studies
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The Environments of Dune: Prophecy through the Gaussian Splat — Julien Hery · (2025) | TGRS Research Map | TGRS