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.
Gaussian-slam: Photo-realistic dense slam with gaussian splatting
11 Pith papers cite this work. Polarity classification is still indexing.
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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 on Replica and +2.23 dB on real hardware at fixed budget.
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 or known intrinsics.
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.
NG-GS uses NeRF guidance and RBF interpolation on 3DGS to produce smoother, higher-quality object segmentation boundaries.
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.
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 and efficiency.
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.
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.
VCS-SLAM introduces geometric validation of semantic observations via visibility consistency, boundary evidence, and ray uncertainty to improve fusion in 3D Gaussian SLAM.
A survey compiling principles, applications, benchmarks, and challenges of 3D Gaussian Splatting for explicit 3D scene representation.
citing papers explorer
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MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction
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.
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GaussLite: Online Task-Conditioned 3D Gaussian Splatting for Real-Time Robotic Mapping
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 on Replica and +2.23 dB on real hardware at fixed budget.
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CoMo3R-SLAM: Collaborative Monocular Dense SLAM with Learned 3D Reconstruction Priors for Outdoor Multi-Agent Systems
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 or known intrinsics.
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WaterSplat-SLAM: Photorealistic Monocular SLAM in Underwater Environment
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.
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NG-GS: NeRF-Guided 3D Gaussian Splatting Segmentation
NG-GS uses NeRF guidance and RBF interpolation on 3DGS to produce smoother, higher-quality object segmentation boundaries.
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Compact 3D Gaussian Splatting For Dense Visual SLAM
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.
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Robust and Efficient Monocular 3D Gaussian SLAM for Kilometer-Scale Outdoor Scenes
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 and efficiency.
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Mono-Hydra++: Real-Time Monocular Scene Graph Construction with Multi-Task Learning for 3D Indoor Mapping
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.
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SING3R-SLAM: Submap-based Indoor Monocular Gaussian SLAM with 3D Reconstruction Priors
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.
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VCS-SLAM: Geometry-Validated Semantic Evidence Fusion for 3D Gaussian SLAM
VCS-SLAM introduces geometric validation of semantic observations via visibility consistency, boundary evidence, and ray uncertainty to improve fusion in 3D Gaussian SLAM.
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A Survey on 3D Gaussian Splatting
A survey compiling principles, applications, benchmarks, and challenges of 3D Gaussian Splatting for explicit 3D scene representation.