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Drone-assisted road gaussian splatting with cross-view uncertainty.arXiv preprint arXiv:2408.15242

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it

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cs.CV 4

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2026 4

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representative citing papers

Sky2Ground: A Benchmark for Site Modeling under Varying Altitude

cs.CV · 2026-03-14 · conditional · novelty 7.0

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.

Visually-grounded Humanoid Agents

cs.CV · 2026-04-09 · unverdicted · novelty 6.0

A coupled world-agent framework uses 3D Gaussian reconstruction and first-person RGB-D perception with iterative planning to enable goal-directed, collision-avoiding humanoid behavior in novel reconstructed scenes.

ABot-Earth 0.5: Generative 3D Earth Model

cs.CV · 2026-06-08 · unverdicted · novelty 4.0

ABot-Earth 0.5 is a 3DGS-based generative model trained on real-world urban reconstructions that synthesizes novel 3D scenes from satellite imagery in under 10 minutes per square kilometer.

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Showing 4 of 4 citing papers after filters.

  • Sky2Ground: A Benchmark for Site Modeling under Varying Altitude cs.CV · 2026-03-14 · conditional · none · ref 53

    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.

  • TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization cs.CV · 2026-05-19 · unverdicted · none · ref 13

    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.

  • Visually-grounded Humanoid Agents cs.CV · 2026-04-09 · unverdicted · none · ref 115

    A coupled world-agent framework uses 3D Gaussian reconstruction and first-person RGB-D perception with iterative planning to enable goal-directed, collision-avoiding humanoid behavior in novel reconstructed scenes.

  • ABot-Earth 0.5: Generative 3D Earth Model cs.CV · 2026-06-08 · unverdicted · none · ref 35

    ABot-Earth 0.5 is a 3DGS-based generative model trained on real-world urban reconstructions that synthesizes novel 3D scenes from satellite imagery in under 10 minutes per square kilometer.