AIBullisharXiv β CS AI Β· Mar 27/1012
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MEGS$^{2}$: Memory-Efficient Gaussian Splatting via Spherical Gaussians and Unified Pruning
Researchers introduce MEGSΒ², a new memory-efficient framework for 3D Gaussian Splatting that reduces memory consumption by 50% for static rendering and 40% for real-time rendering. The breakthrough enables 3D rendering on edge devices by replacing memory-intensive spherical harmonics with lightweight spherical Gaussian lobes and implementing unified pruning optimization.