AI RESEARCH
M^3: Dense Matching Meets Multi-View Foundation Models for Monocular Gaussian Splatting SLAM
arXiv CS.CV
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ArXi:2603.16844v1 Announce Type: new Streaming reconstruction from uncalibrated monocular video remains challenging, as it requires both high-precision pose estimation and computationally efficient online refinement in dynamic environments. While coupling 3D foundation models with SLAM frameworks is a promising paradigm, a critical bottleneck persists: most multi-view foundation models estimate poses in a feed-forward manner, yielding pixel-level correspondences that lack the requisite precision for rigorous geometric optimization.