[3DV 2025, Oral] LoopSplat: Loop Closure by Registering 3D Gaussian Splats
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Updated
Feb 3, 2025 - Python
[3DV 2025, Oral] LoopSplat: Loop Closure by Registering 3D Gaussian Splats
Paper Survey for 3DGS SLAM
RGBD-3DGS-SLAM is a monocular SLAM system leveraging 3D Gaussian Splatting (3DGS) for accurate point cloud and visual odometry estimation. By integrating neural networks, it estimates depth and camera intrinsics from RGB images alone, with optional support for additional camera information and depth maps.
[CVPR 2026] VarSplat: Uncertainty-aware 3D Gaussian Splatting for Robust RGB-D SLAM
[CVPR'26] SGAD-SLAM: Splatting Gaussians at Adjusted Depth for Better Radiance Fields in RGBD SLAM
The official release of Splatonic (HPCA'26), an acceleration framework for 3DGS-SLAM.
Official implementation of TGS-SLAM (RA-L 2026), a semantic RGB-D SLAM system with 3D Gaussians and TriDS. Achieves 97.02% mIoU on Replica with ~100x fewer semantic parameters.
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