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Gaussian-SLAM: Photo-realistic Dense SLAM with Gaussian Splatting

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arxiv 2312.10070 v2 pith:ZHBLEATO submitted 2023-12-06 cs.CV cs.RO

Vladimir Yugay , Yue Li , Theo Gevers , Martin R. Oswald This is my paper
classification cs.CVcs.RO
keywords densephoto-realisticreal-worldrenderingsceneslameffectivegaussian
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We present a dense simultaneous localization and mapping (SLAM) method that uses 3D Gaussians as a scene representation. Our approach enables interactive-time reconstruction and photo-realistic rendering from real-world single-camera RGBD videos. To this end, we propose a novel effective strategy for seeding new Gaussians for newly explored areas and their effective online optimization that is independent of the scene size and thus scalable to larger scenes. This is achieved by organizing the scene into sub-maps which are independently optimized and do not need to be kept in memory. We further accomplish frame-to-model camera tracking by minimizing photometric and geometric losses between the input and rendered frames. The Gaussian representation allows for high-quality photo-realistic real-time rendering of real-world scenes. Evaluation on synthetic and real-world datasets demonstrates competitive or superior performance in mapping, tracking, and rendering compared to existing neural dense SLAM methods.

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Cited by 23 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction

    cs.RO 2026-05 unverdicted novelty 8.0 of 10

    MAGS-SLAM is the first RGB-only multi-agent 3D Gaussian Splatting SLAM framework that matches RGB-D performance via compact submap sharing, geometry-appearance loop verification, and occupancy-aware fusion.

  2. GaussLite: Online Task-Conditioned 3D Gaussian Splatting for Real-Time Robotic Mapping

    cs.CV 2026-06 unverdicted novelty 7.0 of 10

    GaussLite conditions 3D Gaussian Splatting seeding density, gradient flow, and scaling on task relevance masks derived from LLM-parsed natural language and open-vocabulary detection, yielding +2.72 dB ROI PSNR gains o...

  3. CoMo3R-SLAM: Collaborative Monocular Dense SLAM with Learned 3D Reconstruction Priors for Outdoor Multi-Agent Systems

    cs.RO 2026-05 unverdicted novelty 7.0 of 10

    Presents CoMo3R-SLAM, the first collaborative monocular dense RGB SLAM using learned feed-forward 3D priors for outdoor multi-agent systems, achieving competitive accuracy and global consistency without depth sensors ...

  4. WaterSplat-SLAM: Photorealistic Monocular SLAM in Underwater Environment

    cs.RO 2026-04 unverdicted novelty 7.0 of 10

    WaterSplat-SLAM achieves robust camera tracking and high-fidelity rendering in underwater environments by coupling semantic medium filtering into two-view reconstruction and using an online medium-aware Gaussian map.

  5. AGS: Accelerating 3D Gaussian Splatting SLAM via CODEC-Assisted Frame Covisibility Detection

    cs.AR 2025-08 conditional novelty 7.0 of 10

    AGS speeds up 3DGS-SLAM training by measuring frame covisibility from CODEC motion-estimation data, then skipping redundant pose refinements and non-contributory Gaussian computations.

  6. GeoGS-SLAM: Geometry-Only Gaussian Splatting for Dense Monocular SLAM

    cs.RO 2026-07 conditional novelty 6.0 of 10

    GeoGS-SLAM removes appearance parameters from 3D Gaussian Splatting for geometry-only dense monocular SLAM, achieving faster convergence and fewer primitives while introducing a coherent Sim(3) map update for loop closure.

  7. Why does Deep Learning Improve Visual SLAM?

    cs.CV 2026-07 conditional novelty 6.0 of 10

    Learned 2D data association and uncertainty—not recurrent architectures—drive the performance gains of deep visual SLAM, as shown by integrating them into classical ORB-SLAM3.

  8. MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction

    cs.RO 2026-05 conditional novelty 6.0 of 10

    MAGS-SLAM is the first monocular multi-agent Gaussian Splatting SLAM system, aligning independently scaled sub-maps with a Sim(3) pose graph and occupancy-aware Gaussian fusion.

  9. NG-GS: NeRF-Guided 3D Gaussian Splatting Segmentation

    cs.CV 2026-04 unverdicted novelty 6.0 of 10

    NG-GS uses NeRF guidance and RBF interpolation on 3DGS to produce smoother, higher-quality object segmentation boundaries.

  10. RU4D-SLAM: Reweighting Uncertainty in Gaussian Splatting SLAM for 4D Scene Reconstruction

    cs.CV 2026-02 conditional novelty 6.0 of 10

    RU4D-SLAM reweights per-pixel uncertainty to map static and dynamic Gaussians, handling motion blur and exposure shifts, beating previous Gaussian-SLAM on TUM, Bonn, and Wild-SLAM.

  11. Robust 3DGS-based SLAM via Adaptive Kernel Smoothing

    cs.CV 2025-11 conditional novelty 6.0 of 10

    CB-KNN smooths the colors and positions of nearby Gaussians during keyframe rendering and reports modestly lower tracking error on Replica, TUM-RGBD, and ScanNet.

  12. LEGO-SLAM: Language-Embedded Gaussian Optimization SLAM

    cs.CV 2025-11 conditional novelty 6.0 of 10

    A 3D Gaussian Splatting SLAM system learns compact 16-dim language features per Gaussian, enabling real-time open-vocabulary mapping, semantic pruning, and language-based loop closure.

  13. OmniMap: A General Mapping Framework Integrating Optics, Geometry, and Semantics

    cs.RO 2025-09 conditional novelty 6.0 of 10

    OmniMap combines TSDF voxels, 3D Gaussian splatting, and open-vocabulary instance fusion in one online RGB-D mapping system that reports state-of-the-art rendering, mesh, and zero-shot segmentation on Replica and ScanNet.

  14. DINO-SLAM: DINO-informed RGB-D SLAM for Neural Implicit and Explicit Representations

    cs.CV 2025-07 conditional novelty 6.0 of 10

    Geometry-enriched DINO features improve mapping, rendering, and tracking in both NeRF-based and 3D Gaussian splatting SLAM pipelines on indoor benchmarks.

  15. Compact 3D Gaussian Splatting For Dense Visual SLAM

    cs.CV 2024-03 unverdicted novelty 6.0 of 10

    A compact 3D Gaussian Splatting SLAM system reduces Gaussian count and parameter size via masking and a geometry codebook while preserving SOTA reconstruction quality and pose accuracy.

  16. Robust and Efficient Monocular 3D Gaussian SLAM for Kilometer-Scale Outdoor Scenes

    cs.CV 2026-06 unverdicted novelty 5.0 of 10

    KiloGS-SLAM is a monocular 3DGS SLAM system with condition-triggered hybrid tracking and probabilistic chunk-based Gaussian mapping that scales to over 10,000 frames in outdoor environments while maintaining accuracy ...

  17. Mono-Hydra++: Real-Time Monocular Scene Graph Construction with Multi-Task Learning for 3D Indoor Mapping

    cs.RO 2026-05 unverdicted novelty 5.0 of 10

    Mono-Hydra++ is a monocular RGB-IMU pipeline that constructs hierarchical 3D scene graphs in real time while reporting lower trajectory error than some RGB-D baselines on indoor datasets.

  18. DiskChunGS: Large-Scale 3D Gaussian SLAM Through Chunk-Based Memory Management

    cs.RO 2025-11 conditional novelty 5.0 of 10

    Storing inactive spatial chunks of a 3D Gaussian map on disk and loading only camera-visible chunks into GPU memory lets DiskChunGS map all 11 KITTI sequences on a 24 GB GPU without memory failures.

  19. SING3R-SLAM: Submap-based Indoor Monocular Gaussian SLAM with 3D Reconstruction Priors

    cs.CV 2025-11 unverdicted novelty 5.0 of 10

    SING3R-SLAM adds submap-level global alignment and reconstruction priors to a Gaussian map to reduce drift and improve local geometry in monocular indoor SLAM.

  20. UniSpine-GS: An Efficient Physics-Aware Gaussian Framework for Cross-Modality Multi-view Spine Image Synthesis

    cs.CV 2026-07 conditional novelty 4.0 of 10

    A radiative 3D Gaussian model with structure-prior loss reweighting synthesizes consistent multi-view spine projections for CT and ultrasound, beating neural-field baselines in quality and speed.

  21. Mind Meets Space: Rethinking Agentic Spatial Intelligence from a Neuroscience-inspired Perspective

    cs.AI 2025-09 conditional novelty 4.0 of 10

    Agent spatial intelligence is organized into six neuroscience-inspired modules, and the field is reviewed through that lens without any experimental validation.

  22. VCS-SLAM: Geometry-Validated Semantic Evidence Fusion for 3D Gaussian SLAM

    cs.CV 2026-06 unverdicted novelty 3.0 of 10

    VCS-SLAM introduces geometric validation of semantic observations via visibility consistency, boundary evidence, and ray uncertainty to improve fusion in 3D Gaussian SLAM.

  23. A Survey on 3D Gaussian Splatting

    cs.CV 2024-01 unverdicted novelty 2.0 of 10

    A survey compiling principles, applications, benchmarks, and challenges of 3D Gaussian Splatting for explicit 3D scene representation.

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