Sky2Ground provides a new three-view multi-altitude dataset and SkyNet model that improves absolute pose estimation performance by 9.6% on RRA@5 and 18.1% on RTA@5 over prior methods when satellite imagery is included.
Citygs-x: A scalable architecture for efficient and geometrically accurate large-scale scene reconstruction.arXiv preprint arXiv:2503.23044
6 Pith papers cite this work. Polarity classification is still indexing.
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City-Mesh3R reconstructs scalable watertight city-scale 3D meshes from multi-view images via topological clustering, distributed SfM, spatial partitioning, and curvature-aware remeshing.
TideGS scales 3D Gaussian Splatting to over one billion primitives on a single 24 GB GPU by using block-virtualized geometry, asynchronous I/O pipelines, and trajectory-adaptive differential streaming to exploit training sparsity.
A technique reconstructs large urban areas from sparse extreme off-nadir satellite images by modeling geometry as a Z-monotonic 2.5D height map SDF and applying a generative network to restore plausible textures on the resulting mesh.
MetroGS combines distributed 2D Gaussian Splatting with structured dense enhancement, progressive hybrid optimization, and depth-guided appearance modeling to deliver higher geometric accuracy and stability in large-scale urban reconstruction.
DAV-GSWT selects views by diffusion-model uncertainty and hallucinates missing structure so Gaussian Splatting Wang Tiles can be made from sparse captures.
citing papers explorer
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Sky2Ground: A Benchmark for Site Modeling under Varying Altitude
Sky2Ground provides a new three-view multi-altitude dataset and SkyNet model that improves absolute pose estimation performance by 9.6% on RRA@5 and 18.1% on RTA@5 over prior methods when satellite imagery is included.
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City-Mesh3R: Simulation-Ready City-Scale 3D Mesh Reconstruction from Multi-View Images
City-Mesh3R reconstructs scalable watertight city-scale 3D meshes from multi-view images via topological clustering, distributed SfM, spatial partitioning, and curvature-aware remeshing.
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TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization
TideGS scales 3D Gaussian Splatting to over one billion primitives on a single 24 GB GPU by using block-virtualized geometry, asynchronous I/O pipelines, and trajectory-adaptive differential streaming to exploit training sparsity.
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From Orbit to Ground: Generative City Photogrammetry from Extreme Off-Nadir Satellite Images
A technique reconstructs large urban areas from sparse extreme off-nadir satellite images by modeling geometry as a Z-monotonic 2.5D height map SDF and applying a generative network to restore plausible textures on the resulting mesh.
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MetroGS: Efficient and Stable Reconstruction of Geometrically Accurate High-Fidelity Large-Scale Scenes
MetroGS combines distributed 2D Gaussian Splatting with structured dense enhancement, progressive hybrid optimization, and depth-guided appearance modeling to deliver higher geometric accuracy and stability in large-scale urban reconstruction.
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DAV-GSWT: Diffusion-Active-View Sampling for Data-Efficient Gaussian Splatting Wang Tiles
DAV-GSWT selects views by diffusion-model uncertainty and hallucinates missing structure so Gaussian Splatting Wang Tiles can be made from sparse captures.