Evaluation =================================== We evaluate our implementation of Gaussian Splatting (`Splatfacto `_) on the Mip-NeRF 360 dataset, benchmarking it against the original `Inria `_ method. We evaluate all methods with the same resolution (2x downscale) and COLMAP params/undistortion, and we report results at 7,000 and 30,000 steps. All evaluations were executed on an NVIDIA RTX 4090 GPU. .. list-table:: **Time** :widths: 10 10 10 10 10 10 10 10 10 10 :header-rows: 1 * - - Bicycle - Bonsai - Counter - Flowers - Garden - Kitchen - Stump - Treehill - Avg * - inria-7k - 3:34 - 3:27 - 3:05 - 3:02 - 3:51 - 4:00 - 3:25 - 2:53 - 3:24 * - splfacto-7k - 2:36 - 2:18 - 2:06 - 2:14 - 2:49 - 2:17 - 2:24 - 2:23 - 2:23 * - splfacto-big-7k - 3:41 - 3:11 - 2:59 - 2:51 - 3:51 - 3:15 - 2:49 - 2:47 - 3:10 * - inria-30k - 25:07 - 14:37 - 15:24 - 17:32 - 24:03 - 19:02 - 20:25 - 18:02 - 19:17 * - splfacto-30k - 18:03 - 10:13 - 9:07 - 13:25 - 14:58 - 10:02 - 15:15 - 16:56 - 13:30 * - splfacto-big-30k - 31:05 - 13:32 - 13:27 - 22:44 - 26:03 - 16:16 - 21:58 - 25:26 - 21:19 .. list-table:: **PSNR** :widths: 10 10 10 10 10 10 10 10 10 10 :header-rows: 1 * - - Bicycle - Bonsai - Counter - Flowers - Garden - Kitchen - Stump - Treehill - Avg * - inria-7k - 24.11 - 29.49 - 27.16 - 20.54 - 26.53 - 29.02 - 26.74 - 22.50 - 25.76 * - splatfacto-7k - 22.99 - 29.45 - 26.92 - 20.33 - 25.76 - 28.48 - 24.59 - 21.91 - 25.05 * - splatfacto-big-7k - 23.66 - 29.69 - 27.01 - 20.73 - 26.58 - 28.82 - 25.69 - 22.11 - 25.54 * - inria-30k - 25.61 - 31.89 - 28.96 - 21.56 - 27.60 - 31.30 - 25.89 - 22.07 - 26.86 * - splatfacto-30k - 24.99 - 32.14 - 28.72 - 21.54 - 27.31 - 31.18 - 25.64 - 22.28 - 26.73 * - splatfacto-big-30k - 25.7 - 32.23 - 28.95 - 21.96 - 27.83 - 31.6 - 26.7 - 22.38 - 27.17 .. list-table:: **LPIPS** :widths: 10 10 10 10 10 10 10 10 10 10 :header-rows: 1 * - - Bicycle - Bonsai - Counter - Flowers - Garden - Kitchen - Stump - Treehill - Avg * - inria-7k - 0.31 - 0.24 - 0.25 - 0.42 - 0.16 - 0.16 - 0.28 - 0.42 - 0.28 * - splfacto-7k - 0.31 - 0.16 - 0.21 - 0.44 - 0.15 - 0.14 - 0.28 - 0.45 - 0.27 * - splfacto-big-7k - 0.28 - 0.16 - 0.20 - 0.42 - 0.12 - 0.13 - 0.23 - 0.43 - 0.24 * - inria-30k - 0.21 - 0.21 - 0.20 - 0.34 - 0.11 - 0.13 - 0.22 - 0.32 - 0.22 * - splfacto-30k - 0.18 - 0.13 - 0.17 - 0.34 - 0.09 - 0.10 - 0.18 - 0.32 - 0.19 * - splfacto-big-30k - 0.15 - 0.13 - 0.15 - 0.31 - 0.07 - 0.09 - 0.15 - 0.28 - 0.17 .. list-table:: **SSIM** :widths: 10 10 10 10 10 10 10 10 10 10 :header-rows: 1 * - - Bicycle - Bonsai - Counter - Flowers - Garden - Kitchen - Stump - Treehill - Avg * - inria-7k - 0.69 - 0.92 - 0.88 - 0.53 - 0.83 - 0.90 - 0.73 - 0.59 - 0.76 * - splfacto-7k - 0.65 - 0.92 - 0.88 - 0.53 - 0.85 - 0.90 - 0.68 - 0.58 - 0.74 * - splfacto-big-7k - 0.69 - 0.92 - 0.88 - 0.55 - 0.84 - 0.90 - 0.74 - 0.61 - 0.77 * - inria-30k - 0.78 - 0.94 - 0.91 - 0.61 - 0.87 - 0.92 - 0.77 - 0.63 - 0.80 * - splfacto-30k - 0.75 - 0.94 - 0.90 - 0.60 - 0.85 - 0.92 - 0.73 - 0.63 - 0.79 * - splfacto-big-30k - 0.78 - 0.94 - 0.91 - 0.63 - 0.88 - 0.93 - 0.77 - 0.64 - 0.81