arXiv Computer Vision
LinearMask-GS: Stable-Mask Importance Pruning for Compact 3D Gaussian Splatting
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arXiv Computer Vision
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EffGS: Efficient and High-Fidelity Gaussian Splatting
arXiv:2609.39553v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables real-time novel view synthesis, but existing general-purpose acceleration methods suffer severe rendering quality...
Hugging Face Trending Papers
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EffGS: Efficient and High-Fidelity Gaussian Splatting
3D Gaussian Splatting (3DGS) enables real-time novel view synthesis, but existing general-purpose acceleration methods suffer severe rendering quality degradation when extended to more complex, large-...
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Provable Pruning for Efficient 3D Gaussian Splatting via Coresets
arXiv:2607. 02721v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) enables high-quality real-time novel-view synthesis, but practical scenes often contain millions of Gaussians, making compression essential for deployment on limited hardware.
arXiv Computer Vision
6d ago
Gauss What You Need: Compact Gaussian Splatting Across Scene Scales
Gauss What You Need: Compact Gaussian Splatting Across Scene Scales introduces TangoGS, a method that automatically selects the number of Gaussian primitives for 3D Gaussian Splatting by combining capture-derived model sizing with training-based adaptation. The approach first estimates a learning allowance based on the capture’s total pixels, then adjusts the number of Gaussians during training according to reconstruction quality. On standard benchmarks, TangoGS matches the best baseline’s PSNR while using 48% fewer Gaussians, and on larger captures it scales automatically to achieve the highest mean PSNR with 2.3× more Gaussians.
arXiv Computer Vision
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Fast and Compact 3D Gaussian Splatting with Polarized Opacity Prior
arXiv:2608.22344v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) achieves state-of-the-art rendering quality at real-time speeds but suffers from "model bloat" - a large number of redunda...
arXiv Computer Vision
Sep 18
PhGS: Post-Hoc Pruning and Refinement of Single-View Feed-Forward 3D Gaussian Reconstructions
The paper introduces PhGS, a post‑hoc pruning and refinement pipeline for single‑view feed‑forward 3D Gaussian Splatting models. It keeps the base network frozen and applies importance‑score‑based pruning followed by a lightweight recurrent refinement module to reduce spatial redundancy while maintaining rendering quality. The method is backbone‑agnostic, integrates seamlessly with existing baselines, and allows flexible inference‑time keep ratios for different application needs.