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Gaussian-SLAM

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Paper summary

A neural RGBD SLAM method that extends 3D Gaussian Splatting to achieve photorealistic scene reconstruction without sacrificing speed.

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Key points

3D Gaussians for SLAM: Represents scenes as 3D Gaussians rather than neural fields, inheriting the fast training and rendering of Gaussian Splatting.

Photorealistic reconstruction: Produces significantly higher-fidelity reconstructions than prior neural SLAM methods at comparable or better runtime.

RGBD input: Uses standard RGB+depth input streams, making it compatible with off-the-shelf depth cameras for practical deployment.

Speed/quality Pareto: Advances the Pareto frontier for RGBD SLAM, where previous methods forced a trade-off between runtime and photorealism.

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