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+                        We present a work-in-progress survey on 3D Gaussian Splatting compression methods, focusing on their statistical performance across various benchmarks. 
+                        This survey aims to facilitate comparability by summarising key statistics of different compression approaches in a tabulated format. 
+                        The datasets evaluated include TanksAndTemples, MipNeRF360, DeepBlending, and SyntheticNeRF. 
+                        For each method, we report the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Learned Perceptual Image Patch Similarity (LPIPS), and the resultant size in megabytes (MB), as provided by the respective authors. 
+                        This is an ongoing, open project, and we invite contributions from the research community as GitHub issues or pull requests.
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