arXiv:2607. 26219v1 Announce Type: cross Abstract: Regression estimates from observational data can depend on specification under multicollinearity, while sequential sums of squares (SS) depend on term order.
arXiv:2607. 05522v1 Announce Type: cross Abstract: 3D Gaussian splatting (3DGS) is a strong representation for real-time novel-view synthesis, but its standard training pipeline relies on point estimates and hand-tuned heuristics, providing no native uncertainty or principled complexity control.
Hierarchical Incremental Beta Splatting (HIBS) introduces beta kernels into online 3D Gaussian splatting, allowing the shape parameter to interpolate between soft Gaussian-like primitives and flat-topped, near-opaque surfels. This confidence-aware spawning uses geometric observability and multi-view depth agreement to initialize opacity and shape, producing solid primitives where geometry is verifiable and soft, correctable primitives elsewhere. HIBS also employs error-driven relocation for densification, bounded beta kernel support for efficient culling and rasterization, and a shape-preserving merging formulation to create a level-of-detail hierarchy, achieving up to 0.8 dB PSNR improvement and 40 % faster optimization on the Mip-NeRF 360 dataset.
3D Gaussian Splatting (3DGS) renders novel views in real time, but an uncertainty heatmap does not certify that a rendered view meets a certain prediction coverage. We treat novel-view synthesis as st...
Repeated evaluation can estimate a benchmark score accurately while still requiring replication to certify narrow uncertainty. We characterize that requirement on a fixed grid of $M$ tasks with $L$ binary paths per task under the hard budget $(M+t)K$, where each path costs at most $K$ responses or episodes.
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...
arXiv:2608.21008v1 Announce Type: new Abstract: Mobile AR frameworks attach a metric pose prior to every casual phone capture, and turning it into reconstruction-grade poses cheaply on CPU is the ste...
arXiv:2608.28715v1 Announce Type: cross Abstract: Ultrasound-guided interventions can require localization of an untracked 2D frame within a 3D anatomical reference. Rigid slice-to-volume registratio...
Dynamic-scene reconstruction is almost always evaluated inside the observed time window, yet deployment settings such as AR overlays, robot interaction, and anticipatory planning need the future surface: the geometry at times beyond those captured. No standard benchmark measures this.
arXiv:2610.34819v1 Announce Type: new Abstract: Monocular observations of a tumbling object can support a precise fitted trajectory without establishing that the recovered physical axis is correct. W...
arXiv:2609. 29140v1 Announce Type: new Abstract: Repeated evaluation can estimate a benchmark score accurately while still requiring replication to certify narrow uncertainty.
arXiv:2606. 18861v1 Announce Type: cross Abstract: Reconstructing simulation-ready digital twins of articulated objects from sensor observations remains constrained by two persistent gaps: (i) part-level geometric reconstruction is decoupled from kinematic-parameter estimation, and (ii) the recovered models often violate basic dynamic invariants such as energy conservation, leading to drift when the URDF is replayed in physics simulators.
arXiv:2608.29680v1 Announce Type: new Abstract: Feed-forward 3D foundation models reconstruct perspective scenes in one pass. Satellite photogrammetry needs a different product, one that domain adapt...