BathyFacto modifies Nerfacto to trace refracted rays through air and water using Snell's law and a kinked density wrapper, achieving 0.06 m Cloud-to-Mesh distance and 87% completeness on simulated bathymetry data versus 0.52 m and 29% for the baseline.
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A Method for Registration of 3-D Shapes
10 Pith papers cite this work, alongside 13,863 external citations. Polarity classification is still indexing.
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Manifold k-NN generalizes DP-NNS to k-NN queries on manifold point clouds via a recursive successor-list property, delivering 1-10x speedups and full dynamic support.
Sub-metre lunar DEMs were produced from OHRC multi-view images via open-source stereo matching and validated against LRO NAC terrain with 5.85 m vertical RMSE and sub-pixel horizontal accuracy.
SPN is a CNN that detects a spacecraft bounding box, classifies then regresses attitude, and optimizes position via Gauss-Newton, achieving degree-level attitude and cm-level position errors on real images after training only on synthetic data.
Subject-specific fMRI embeddings learned unsupervised from the Natural Scenes Dataset can be aligned across individuals via orthogonal rotations, supporting a shared neural geometry in visual cortex.
Point cloud geometry is cast as a statistical manifold of per-point Gaussians, with POLI learning the mapping self-supervisedly to improve perception without labeled data.
ProBA replaces rigid point tracks with a probabilistic pose graph and 3D Gaussian landmarks, optimizing via negative log-likelihood with the Bhattacharyya coefficient to expand the basin of attraction in prior-free SfM.
UAV LiDAR workflow applies RandLA-Net segmentation and grid elevation differencing to detect slope hazards and monitor deformation on expressways.
A multimodal registration pipeline models splints as rigid mandible transformations to quantify TMJ configuration changes via error propagation and surface metrics.
DigiForest integrates heterogeneous autonomous robots for data collection, automated tree trait extraction, a decision support system for growth forecasting, and autonomous harvesters for selective logging, with real-world tests in European forests.
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Manifold k-NN: Accelerated k-NN Queries for Manifold Point Clouds
Manifold k-NN generalizes DP-NNS to k-NN queries on manifold point clouds via a recursive successor-list property, delivering 1-10x speedups and full dynamic support.