Florian Hahlbohm — accepted AI-conference papers

2026

Faster-GS: Analyzing and Improving Gaussian Splatting Optimization

Florian Hahlbohm, Linus Franke, Martin Eisemann, Marcus Magnor

CVPR 2026

Recent advances in 3D Gaussian Splatting (3DGS) have focused on accelerating optimization while preserving reconstruction quality. However, many proposed methods entangle implementation-level improvements with fundamental algorithmic modifications or trade performance for fidelity, leading to a frag

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2026

NVGS: Neural Visibility for Occlusion Culling in 3D Gaussian Splatting

Brent Zoomers, Florian Hahlbohm, Joni Vanherck, Lode Jorissen, Marcus Magnor, Nick Michiels

CVPR 2026

3D Gaussian Splatting can exploit frustum culling and level-of-detail strategies to accelerate rendering of scenes containing a large number of primitives. However, the semi-transparent nature of Gaussians prevents the application of another highly effective technique: occlusion culling. We address

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