MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors
Riku Murai, Eric Dexheimer, Andrew J. Davison
Abstract
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.
BibTeX
@InProceedings{Murai_2025_CVPR,
author = {Murai, Riku and Dexheimer, Eric and Davison, Andrew J.},
title = {MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors},
booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
month = {June},
year = {2025},
pages = {16695-16705}
}