GlobalSplat achieves competitive novel-view synthesis on RealEstate10K and ACID using only 16K Gaussians via global scene tokens and coarse-to-fine training, with a 4MB footprint and under 78ms inference.
GoDe: Gaussians on demand for progressive level of detail and scalable compression
5 Pith papers cite this work. Polarity classification is still indexing.
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PD-4DGS decomposes 4DGS into static scaffold, global deformation, and local refinement layers using hierarchical decomposition and custom losses, achieving over 60% bitstream reduction and reducing first-frame latency to about 1.7 seconds on 2 Mbps links.
PointSplat uses 3D-geometry-only pruning and a dual-branch transformer to reduce Gaussian count in 3DGS scenes, delivering competitive quality and better efficiency without per-scene fine-tuning.
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.
citing papers explorer
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GlobalSplat: Efficient Feed-Forward 3D Gaussian Splatting via Global Scene Tokens
GlobalSplat achieves competitive novel-view synthesis on RealEstate10K and ACID using only 16K Gaussians via global scene tokens and coarse-to-fine training, with a 4MB footprint and under 78ms inference.
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PD-4DGS:Progressive Decomposition of 4D Gaussian Splatting for Bandwidth-Adaptive Dynamic Scene Streaming
PD-4DGS decomposes 4DGS into static scaffold, global deformation, and local refinement layers using hierarchical decomposition and custom losses, achieving over 60% bitstream reduction and reducing first-frame latency to about 1.7 seconds on 2 Mbps links.
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PointSplat: Efficient Geometry-Driven Pruning and Transformer Refinement for 3D Gaussian Splatting
PointSplat uses 3D-geometry-only pruning and a dual-branch transformer to reduce Gaussian count in 3DGS scenes, delivering competitive quality and better efficiency without per-scene fine-tuning.
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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.