Msa-Splatting: Multi-Scale Adaptive Gaussian Splatting for High-Fidelity View Synthesis

3D Gaussian Splatting (3DGS) has revolutionized novel view synthesis with real-time rendering and high-quality reconstruction. However, its performance degrades under varying scales, causing aliasing and dilation artifacts. To address these challenges, we introduce Msa-Splatting, an enhanced adaptive Gaussian splatting method designed for high-fidelity multi-scale novel view synthesis. Our approach reimagines the Gaussian adaptive control process with a novel multi-fold splitting and cloning mechanism, which optimizes Gaussian properties and reduces spurious artifacts by halving the densification frequency. We further mitigate aliasing in scaled-down renderings with a weighted alpha blending sampling technique, ensuring accurate representation of high-frequency details. To eliminate scale-mismatch artifacts, we introduce 2D variable dilation Gaussians, which dynamically adjust dilation based on the rendering scale. Msa-Splatting significantly enhances the fidelity and adaptability of Gaussian-based rendering, achieving state-of-the-art performance in multi-scale novel view synthesis. Extensive quantitative and qualitative evaluations demonstrate the efficacy of our approach, showcasing its ability to produce perceptually superior renderings with reduced artifacts across varying scales, thus establishing a robust framework for future advancements in scalable rendering technologies.