MCGS-SLAM

A Multi-Camera SLAM Framework Using Gaussian Splatting for High-Fidelity Mapping

Anonymous Author
Code and data [Available Upon Acceptance]

SLAM System Pipeline

Our method performs real-time SLAM by fusing synchronized inputs from a multi-camera rig into a unified 3D Gaussian map. It first selects keyframes and estimates depth and normal maps for each camera, then jointly optimizes poses and depths via multi-camera bundle adjustment and scale-consistent depth alignment. Refined keyframes are fused into a dense Gaussian map using differentiable rasterization, interleaved with densification and pruning. An optional offline stage further refines camera trajectories and map quality. The system supports RGB inputs, enabling accurate tracking and photorealistic reconstruction.

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Analysis of Single-Camera and Multi-Camera SLAM (Mapping)

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This string typically appears as a random sequence or an obscure machine-generated filename. 🔍 Probable Origins of the Filename Download n1c07 txt

If you found a reference to this specific file on a third-party downloading site or noticed it generated on your computer, apply these safety measures: O3 Victoria Tug Co Ltd\n10'0>3 Royal Mail Steam

Many diagnostic programs, automated network scanners, or server scripts automatically generate text files with timestamps or unique hashes that yield similar random filenames. automated network scanners

Files with arbitrary names on file-sharing sites are often vehicles for malware.

Obfuscated or randomly generated alphanumeric strings (like n1c07 ) are frequently used by malware or trojans to drop temporary executable or log files on a local drive.

Analysis of Single-Camera and Multi-Camera SLAM (Tracking)

In this section, we benchmark tracking accuracy across eight driving sequences from the Waymo dataset (Real World). MCGS-SLAM achieves the lowest average ATE, significantly outperforming single-camera methods.
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We further evaluate tracking on four sequences from the Oxford Spires dataset (Real World). MCGS-SLAM consistently yields the best performance, demonstrating robust trajectory estimation in large-scale outdoor environments.
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