arXiv Computer Vision
METRIC-GS: Selective Metric-Scale Estimation for 3D Gaussian Splatting
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arXiv Computer Vision
Sep 18
SlugTrails: An Egocentric Benchmark for Floor Plan Localization in Large Buildings
SlugTrails is a new egocentric benchmark for floor‑plan‑based indoor visual localization in large buildings, featuring 30 Hz Aria glasses recordings across three campus buildings and six floors. The dataset includes CAD‑derived floor plans with semantic classes, circulation masks, and laser‑surveyed anchors for trajectory alignment. Five representative systems were evaluated, showing that stock checkpoints perform poorly while fine‑tuning on SlugTrails significantly improves performance and cross‑dataset generalization, indicating that data scarcity limits current methods.
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
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.
Hugging Face Trending Papers
Sep 17
SlugTrails: An Egocentric Benchmark for Floor Plan Localization in Large Buildings
SlugTrails is a new egocentric benchmark for floor‑plan‑based indoor visual localization in large buildings, featuring 30 Hz Aria glasses recordings across three campus buildings and six floors (22 089 m²). The dataset includes CAD‑derived floor plans with semantic classes, circulation masks, and laser‑surveyed anchors, and supports three realistic sensing protocols: single walking frames, stationary multi‑view sweeps, and walking streams with odometry. Evaluation of five geometric and learned systems shows that stock models perform poorly, but fine‑tuning on SlugTrails significantly improves performance and cross‑dataset generalization, indicating that data scarcity limits current localization methods.
arXiv Machine Learning
Aug 4
Posterior Variance Is a Constraint Map, Not an Error Map: Closed-Form Uncertainty for Radiative Gaussian Splatting in Sparse-View CT
arXiv:2607. 13682v2 Announce Type: cross Abstract: Radiative Gaussian splatting reconstructs sparse-view CT fast and accurately, and recent work attaches per-Gaussian posteriors to yield per-voxel uncertainty maps.
arXiv Computer Vision
Sep 10
View-Structured Conformal Prediction for 3D Gaussian Splatting
arXiv:2609.10307v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) renders novel views in real time, but an uncertainty heatmap does not certify that a rendered view meets a certain predi...