GETA-3DGS is the first automatic joint structured pruning and quantization framework for 3D Gaussian Splatting, achieving roughly 5x storage reduction on standard datasets without per-scene thresholds.
gsplat: An open-source library for gaussian splatting.ArXiv, abs/2409.06765
6 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 6representative citing papers
Bit flips in 3D Gaussian splatting are highly concentrated in effect with certain high-order bits corrupting up to 75.7% of the frame, but a support guard reduces the worst footprint to 11.68% while preserving clean performance and improving quality under accumulated faults.
An end-to-end transcoding pipeline creates 3D Gaussian splatting models from plenoptic point clouds or meshes without original multi-view images, using custom initialization and surface constraints for high-quality output with fewer splats and faster convergence.
Current densification methods in 3D Gaussian Splatting do not significantly benefit from dense initializations and perform similarly to sparse SfM-based ones.
Proposes a physics-based 3D Gaussian framework that disentangles appearance from medium effects for high-quality underwater novel view synthesis and scene restoration.
Turbo-GS accelerates 3D Gaussian Splatting training via dilated rendering of pixel subsets, convergence-aware Gaussian budget allocation, and combined positional-appearance error densification to enable faster 4K fitting with preserved or improved rendering quality.
citing papers explorer
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3D-UIR: 3D Gaussian for Underwater 3D Scene Reconstruction via Physics Based Appearance-Medium Decoupling
Proposes a physics-based 3D Gaussian framework that disentangles appearance from medium effects for high-quality underwater novel view synthesis and scene restoration.