MEGS$^{2}$: Memory-Efficient Gaussian Splatting via Spherical Gaussians and Unified Pruning

Researchers introduce MEGS², 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.