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arxiv: 2501.06897 · v3 · pith:QGJWDWXB · submitted 2025-01-12 · cs.CV · cs.RO

ActiveGAMER: Active GAussian Mapping through Efficient Rendering

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classification cs.CV cs.RO
keywords mappingactiveactivegamerefficientexplorationsystemaccuracycompleteness
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We introduce ActiveGAMER, an active mapping system that utilizes 3D Gaussian Splatting (3DGS) to achieve high-quality, real-time scene mapping and exploration. Unlike traditional NeRF-based methods, which are computationally demanding and restrict active mapping performance, our approach leverages the efficient rendering capabilities of 3DGS, allowing effective and efficient exploration in complex environments. The core of our system is a rendering-based information gain module that dynamically identifies the most informative viewpoints for next-best-view planning, enhancing both geometric and photometric reconstruction accuracy. ActiveGAMER also integrates a carefully balanced framework, combining coarse-to-fine exploration, post-refinement, and a global-local keyframe selection strategy to maximize reconstruction completeness and fidelity. Our system autonomously explores and reconstructs environments with state-of-the-art geometric and photometric accuracy and completeness, significantly surpassing existing approaches in both aspects. Extensive evaluations on benchmark datasets such as Replica and MP3D highlight ActiveGAMER's effectiveness in active mapping tasks.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Uncertainty-driven 3D Gaussian Splatting Active Mapping via Anisotropic Visibility Field

    cs.CV 2026-05 unverdicted novelty 6.0

    GAVIS quantifies per-particle anisotropic visibility in 3DGS via spherical harmonics, integrates it into a Bayesian rasterizer for real-time uncertainty, and uses maximum information gain for active mapping.