A plug-and-play perceptual wrapper using common random noise and Wasserstein Distortion supervision improves texture quality and reduces model size in 3D Gaussian Splatting.
Hemgs: A hybrid entropy model for 3d gaussian splatting data compression
5 Pith papers cite this work, alongside 2 external citations. Polarity classification is still indexing.
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Iterative Gaussian Synopsis creates compact multi-level LOD hierarchies for 3D Gaussian Splatting via top-down unfolding with adaptive pruning, preserving quality while cutting storage.
NiFi applies artifact-aware, diffusion-based one-step distillation to compress 3D Gaussian Splatting to 0.1 MB while claiming state-of-the-art perceptual quality and up to 1000x rate reduction.
MesonGS++ achieves over 34x compression of 3D Gaussian Splatting models post-training while preserving or exceeding original rendering quality through size-aware hyperparameter optimization.
Scene-adaptive lattice vector quantization improves rate-distortion performance of 3DGS compression over uniform scalar quantization while adding little overhead and supporting multiple bit rates from one trained model.
citing papers explorer
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Seeing What Matters: Perceptual Wrapper with Common Randomness for 3D Gaussian Splatting
A plug-and-play perceptual wrapper using common random noise and Wasserstein Distortion supervision improves texture quality and reduces model size in 3D Gaussian Splatting.
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Unfolding 3D Gaussian Splatting via Iterative Gaussian Synopsis
Iterative Gaussian Synopsis creates compact multi-level LOD hierarchies for 3D Gaussian Splatting via top-down unfolding with adaptive pruning, preserving quality while cutting storage.
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Nix and Fix: Targeting 1000x Compression of 3D Gaussian Splatting with Diffusion Models
NiFi applies artifact-aware, diffusion-based one-step distillation to compress 3D Gaussian Splatting to 0.1 MB while claiming state-of-the-art perceptual quality and up to 1000x rate reduction.
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MesonGS++: Post-training Compression of 3D Gaussian Splatting with Hyperparameter Searching
MesonGS++ achieves over 34x compression of 3D Gaussian Splatting models post-training while preserving or exceeding original rendering quality through size-aware hyperparameter optimization.
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Improving 3D Gaussian Splatting Compression by Scene-Adaptive Lattice Vector Quantization
Scene-adaptive lattice vector quantization improves rate-distortion performance of 3DGS compression over uniform scalar quantization while adding little overhead and supporting multiple bit rates from one trained model.