AGILE-GS: Anchor-Guided Fast Next-Best-View Selection for Active 3D Gaussian Splatting

arXiv:2609.34176 · cs.CV, cs.RO · Submitted 2026-09-28 · Read on arXiv

cs.CV, cs.RO

Submitted: 2026-09-28

Updated: 2026-09-28

Terminology

• Gaussian Splatting — 17× in this paper · explained in 4 episodes
• 3D Gaussian Splatting — 12× in this paper · explained in 2 episodes
• Information Gain — 11× in this paper · explained in 2 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Benchmark — 8× in this paper · explained in 2 episodes
• Fisher Information — 8× in this paper · explained in 3 episodes
• Active Perception — 4× in this paper · explained in 2 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• 3D Gaussian Splatting (3DGS) — 2× in this paper · explained in 4 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Active Learning — 2× in this paper · explained in 6 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Fidelity — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Active Vision — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Digital Twin — 1× in this paper · explained in 4 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Online Row Sampling
• Bayesian Active Learning for Classification and Preference Learning
• Active Next-Best-View Optimization for Risk-Averse Path Planning
• Splat-CBF: Safe Next-Best-View Control in 3D Gaussian-Splat Maps
• Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities
• Conflict-Aware Active Perception and Control in 3D Gaussian Splatting Fields via Control Barrier Functions

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