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GlORIE-SLAM: Globally Optimized RGB-only Implicit Encoding Point Cloud SLAM

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arxiv 2403.19549 v3 pith:RTS62423 submitted 2024-03-28 cs.CV cs.RO

GlORIE-SLAM: Globally Optimized RGB-only Implicit Encoding Point Cloud SLAM

Ganlin Zhang , Erik Sandstr\"om , Youmin Zhang , Manthan Patel , Luc Van Gool , Martin R. Oswald This is my paper
classification cs.CV cs.RO
keywords slamdepthrgb-onlydenseneuraladjustmentbundlecloud
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Recent advancements in RGB-only dense Simultaneous Localization and Mapping (SLAM) have predominantly utilized grid-based neural implicit encodings and/or struggle to efficiently realize global map and pose consistency. To this end, we propose an efficient RGB-only dense SLAM system using a flexible neural point cloud scene representation that adapts to keyframe poses and depth updates, without needing costly backpropagation. Another critical challenge of RGB-only SLAM is the lack of geometric priors. To alleviate this issue, with the aid of a monocular depth estimator, we introduce a novel DSPO layer for bundle adjustment which optimizes the pose and depth of keyframes along with the scale of the monocular depth. Finally, our system benefits from loop closure and online global bundle adjustment and performs either better or competitive to existing dense neural RGB SLAM methods in tracking, mapping and rendering accuracy on the Replica, TUM-RGBD and ScanNet datasets. The source code is available at https://github.com/zhangganlin/GlOIRE-SLAM

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Forward citations

Cited by 4 Pith papers

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

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

    cs.RO 2026-04 unverdicted novelty 7.0

    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.

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

    cs.RO 2026-07 conditional novelty 6.0

    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.

  3. BA-T: An Iterative Transformer for Two-View Bundle Adjustment

    cs.CV 2026-06 unverdicted novelty 6.0

    BA-T is an iterative Transformer that implements bundle adjustment as a repeatable lightweight layer to progressively refine pose and geometry predictions in two-view 3D reconstruction while using far fewer decoder pa...

  4. WildPose: A Unified Framework for Robust Pose Estimation in the Wild

    cs.CV 2026-05 unverdicted novelty 5.0

    WildPose unifies feedforward 3D features from MASt3R with differentiable bundle adjustment for robust monocular pose estimation across dynamic, static, and low-ego-motion scenes.