MR.ScaleMaster: Scale-Consistent Collaborative Mapping from Crowd-Sourced Monocular Videos

arXiv:2604.11372 · cs.RO · Submitted 2026-04-13 · Read on arXiv

cs.RO

Submitted: 2026-04-13

Updated: 2026-09-23

Code: https://github.com/team-aprl/MR.ScaleMaster

Terminology

• Failure Modes — 7× in this paper · explained in 3 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Foundation Model — 4× in this paper · explained in 3 episodes
• Foundation Models — 4× in this paper · explained in 7 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Degeneracy — 3× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Absolute Trajectory Error — 1× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Gauge Freedom — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Simultaneous Localization and Mapping — 1× in this paper
• Transformer — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• $\pi^3$: Permutation-Equivariant Visual Geometry Learning
• VGGT-SLAM 2.0: Real-time Dense Feed-forward Scene Reconstruction
• Multi-Agent Monocular Dense SLAM With 3D Reconstruction Priors
• VGGT-Long: Chunk it, Loop it, Align it -- Pushing VGGT's Limits on Kilometer-scale Long RGB Sequences
• COVINS-G: A Generic Back-end for Collaborative Visual-Inertial SLAM

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