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.
Compression in 3D Gaussian splatting: A survey of methods, trends, and future directions
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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.
A survey that categorizes and summarizes methods applying 3D Gaussian Splatting to segmentation, editing, generation, and related tasks, including datasets and evaluation protocols.
citing papers explorer
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GETA-3DGS: Automatic Joint Structured Pruning and Quantization for 3D Gaussian Splatting
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.
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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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A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation
A survey that categorizes and summarizes methods applying 3D Gaussian Splatting to segmentation, editing, generation, and related tasks, including datasets and evaluation protocols.