Flux-GS is a mobile-optimized 3D Gaussian Splatting method that compresses specular energy via Monte Carlo aggregation, recovers details with attribute-conditioned SH offsets, and uses multi-view guidance for densification to cut parameters while keeping visual quality.
Megs2: Memory-efficient gaussian splatting via spherical gaussians and unified pruning
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POTR introduces simultaneous-effect pruning via a modified 3DGS rasterizer and entropy-reducing lighting coefficient recomputation to outperform prior post-training 3DGS compression methods in rate-distortion and inference speed.
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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Monte Carlo Energy Aggregation for Mobile 3D Gaussian Splatting
Flux-GS is a mobile-optimized 3D Gaussian Splatting method that compresses specular energy via Monte Carlo aggregation, recovers details with attribute-conditioned SH offsets, and uses multi-view guidance for densification to cut parameters while keeping visual quality.
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POTR: Post-Training 3DGS Compression
POTR introduces simultaneous-effect pruning via a modified 3DGS rasterizer and entropy-reducing lighting coefficient recomputation to outperform prior post-training 3DGS compression methods in rate-distortion and inference speed.
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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.