The paper "Analytic-Splatting: Anti-Aliased 3D Gaussian Splatting via Analytic Integration" addresses the issue of aliasing in 3D Gaussian Splatting (3DGS), a method used for novel view synthesis. 3DGS combines the advantages of primitive-based and volumetric 3D representations, but it suffers from aliasing when rendering at varying resolutions. The authors derive an analytical solution to improve anti-aliasing and detail fidelity. They use a conditioned logistic function to approximate the cumulative distribution function (CDF) of a one-dimensional Gaussian signal and calculate the Gaussian integral within a 2D pixel window area. This approach is then applied to the 2D pixel shading process, resulting in Analytic-Splatting. The method is evaluated on various datasets, demonstrating superior anti-aliasing capabilities and better detail fidelity compared to other methods. The paper also includes a detailed technical background, method description, and experimental results, showing the effectiveness of the proposed approach.The paper "Analytic-Splatting: Anti-Aliased 3D Gaussian Splatting via Analytic Integration" addresses the issue of aliasing in 3D Gaussian Splatting (3DGS), a method used for novel view synthesis. 3DGS combines the advantages of primitive-based and volumetric 3D representations, but it suffers from aliasing when rendering at varying resolutions. The authors derive an analytical solution to improve anti-aliasing and detail fidelity. They use a conditioned logistic function to approximate the cumulative distribution function (CDF) of a one-dimensional Gaussian signal and calculate the Gaussian integral within a 2D pixel window area. This approach is then applied to the 2D pixel shading process, resulting in Analytic-Splatting. The method is evaluated on various datasets, demonstrating superior anti-aliasing capabilities and better detail fidelity compared to other methods. The paper also includes a detailed technical background, method description, and experimental results, showing the effectiveness of the proposed approach.