Tobias Alexander Franke

STAR-NT: Spatiotemporal Acceleration of Real-Time Neural Transparency Rendering

Grigoris Tsopouridis, Christos Georgiou-Mousses, Aris Panagiotidis, Andreas Vasilakis, David Corrigan, Tobias Alexander Franke, Aleksei Gorbonosov, Andrei Astapov, and Ioannis Fudos Proceedings of Computer Graphics International 2026

Quality comparison of methods: FLIP mean error (white) and MSE * 10<sup>2</sup> (green). The ground truth is shown on the left with the depth complexity (maximum number of transparent layers) in the parenthesis.
Quality comparison of methods: FLIP mean error (white) and MSE * 102 (green). The ground truth is shown on the left with the depth complexity (maximum number of transparent layers) in the parenthesis.

Abstract

Neural order-independent transparency delivers high-quality rendering of overlapping transparent surfaces, but its geometry passes and network input generation remain costly, particularly on mobile and legacy hardware. We present a spatiotemporal acceleration framework that exploits spatial and temporal coherence to reduce this overhead while preserving visual quality. Spatially, we use adaptive quadtree-based screen-space subdivision to scale geometry pass resolution according to local color variance. Temporally, selected frames reuse the previous transparency result through depth-based reprojection instead of full rendering. Together, these optimizations reduce rendering cost and integrate efficiently into existing real-time rendering pipelines.

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Links

 2026-06-15
 Conference Publication STAR Neural Rendering Transparency
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