SOURCE-LINKED INTELLIGENCE
CVT-GS: Learning to Simplify 3D Gaussian Splatting with Centroidal Voronoi Tessellation
While 3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time novel view synthesis, rendering high-fidelity scenes often relies on a massive number of Gaussian primitives, incurring substantial storage and computational overhead. Existing simplification techniques are largely intrusive, requiring training-time pruning, architectural modifications, or computationally expensive per-scene fine-tuning. These drawbacks limit their deployment on off-the-shelf pretrained models. In this paper, we propose CVT-GS, a novel optimization-free post-hoc simplification framework t
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T13:26:32.000Z
First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.