arXiv Computer Vision
KoalaGS: Complexity-Aware Continuous Level of Detail for Gaussian Splatting
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arXiv Computer Vision
Oct 5
Budgeted-GS: Real-Time Large-Scale Gaussian Splatting via Factoring LOD
Budgeted-GS is a post‑hoc technique that transforms any trained 3D Gaussian Splatting model into a factoring tree—a multi‑resolution hierarchy of moment‑matched aggregates. After a brief construction pass, a single quality parameter selects the appropriate level of detail for each view, allowing the same city‑scale model to run in real time on GPUs with varying memory capacities. The method also informs budget‑centered training, enabling models to be built directly at the necessary size and avoiding wasted optimization of later discarded primitives.
arXiv Computer Vision
Sep 28
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
6d ago
LoBE-GS: Load-Balanced and Efficient 3D Gaussian Splatting for Large-Scale Scene Reconstruction
LoBE-GS is a Load‑Balanced and Efficient 3D Gaussian Splatting framework designed for large‑scale scene reconstruction. It introduces a load‑balanced KD‑tree partitioning scheme that balances camera counts per block, uses depth‑based back‑projection to speed up camera assignment, and applies visibility cropping and selective densification to cut training costs. Experiments on urban and outdoor datasets show up to an order‑of‑magnitude faster scene‑partitioning and a 3.2× reduction in worst‑block fine‑training time compared to CityGaussian, while keeping reconstruction quality competitive.
arXiv Computer Vision
Oct 1
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...
arXiv Machine Learning
Jul 7
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.
Hugging Face Trending Papers
Sep 30
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-...