SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM

arXiv:2312.02126v2 Announce Type: replace
Abstract: Dense simultaneous localization and mapping (SLAM) is crucial for robotics and augmented reality applications. However, current methods are often hampered by the non-volumetric or implicit way they represent a scene. This work introduces SplaTAM, an approach that, for the first time, leverages explicit volumetric representations, i.e., 3D Gaussians, to enable high-fidelity reconstruction from a single unposed RGB-D camera, surpassing the capabilities of existing methods. SplaTAM employs a simple online tracking and mapping system tailored to …

abstract applications arxiv augmented reality cs.ai cs.cv cs.ro current however localization map mapping reality rgb-d robotics slam type work