Papers › MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors

MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors

16 Dec 2024CVPR 2025 1arXiv:2412.12392archive 2025-07-28

Riku Murai, Eric Dexheimer, Andrew J. Davison

We present a real-time monocular dense SLAM system designed bottom-up from MASt3R, a two-view 3D reconstruction and matching prior. Equipped with this strong prior, our system is robust on in-the-wild video sequences despite making no assumption on a fixed or parametric camera model beyond a unique camera centre. We introduce efficient methods for pointmap matching, camera tracking and local fusion, graph construction and loop closure, and second-order global optimisation. With known calibration, a simple modification to the system achieves state-of-the-art performance across various benchmarks. Altogether, we propose a plug-and-play monocular SLAM system capable of producing globally-consistent poses and dense geometry while operating at 15 FPS.

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merge_config rmurai0610/mast3r-slam/mast3r_slam/config.py community (archive-listed) ran · our draft was wrong licence not identified · pointer only · d82830fded80479e · report
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