# Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments

arXiv: https://arxiv.org/abs/2012.04746 · HTML: https://mlsanity.com/paper/2012.04746/

## Key facts

- Cited by 19 papers in the map (data through 7 Oct 2026).
- First posted on arXiv 8 Dec 2020.

## Built on by (most cited first, 19 of 19)

- [Visual Localization via Few-Shot Scene Region Classification](https://mlsanity.com/paper/2208.06933/) (2022)
- [Projective Manifold Gradient Layer for Deep Rotation Regression](https://mlsanity.com/paper/2110.11657/) (2021)
- [Interaction Replica: Tracking Human-Object Interaction and Scene Changes From Human Motion](https://mlsanity.com/paper/2205.02830/) (2022)
- [LIP-Loc: LiDAR Image Pretraining for Cross-Modal Localization](https://mlsanity.com/paper/2312.16648/) (2023)
- [Deep Learning for Visual Localization and Mapping: A Survey](https://mlsanity.com/paper/2308.14039/) (2023)
- [CrowdDriven: A New Challenging Dataset for Outdoor Visual Localization](https://mlsanity.com/paper/2109.04527/) (2021)
- [LightLoc: Learning Outdoor LiDAR Localization at Light Speed](https://mlsanity.com/paper/2503.17814/) (2025)
- [A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation](https://mlsanity.com/paper/2303.01743/) (2023)
- [Improving Feature-based Visual Localization by Geometry-Aided Matching](https://mlsanity.com/paper/2211.08712/) (2022)
- [Lazy Visual Localization via Motion Averaging](https://mlsanity.com/paper/2307.09981/) (2023)
- [Towards Robust Probabilistic Modeling on SO(3) via Rotation Laplace Distribution](https://mlsanity.com/paper/2305.10465/) (2023)
- [SG-NeRF: Neural Surface Reconstruction with Scene Graph Optimization](https://mlsanity.com/paper/2407.12667/) (2024)
- [CPO: Change Robust Panorama to Point Cloud Localization](https://mlsanity.com/paper/2207.05317/) (2022)
- [Reprojection Errors as Prompts for Efficient Scene Coordinate Regression](https://mlsanity.com/paper/2409.04178/) (2024)
- [Multi-modal Visual Place Recognition in Dynamics-Invariant Perception Space](https://mlsanity.com/paper/2105.07800/) (2021)
- [6D Camera Relocalization in Visually Ambiguous Extreme Environments](https://mlsanity.com/paper/2207.06333/) (2022)
- [HyperPose: Hypernetwork-Infused Camera Pose Localization and an Extended Cambridge Landmarks Dataset](https://mlsanity.com/paper/2303.02610/) (2023)
- [Graph Attention Network for Camera Relocalization on Dynamic Scenes](https://mlsanity.com/paper/2209.15056/) (2022)
- [Robust SG-NeRF: Robust Scene Graph Aided Neural Surface Reconstruction](https://mlsanity.com/paper/2411.13620/) (2024)

## Abstract (arXiv)

Localizing the camera in a known indoor environment is a key building block for scene mapping, robot navigation, AR, etc. Recent advances estimate the camera pose via optimization over the 2D/3D-3D correspondences established between the coordinates in 2D/3D camera space and 3D world space. Such a mapping is estimated with either a convolution neural network or a decision tree using only the static input image sequence, which makes these approaches vulnerable to dynamic indoor environments that are quite common yet challenging in the real world. To address the aforementioned issues, in this paper, we propose a novel outlier-aware neural tree which bridges the two worlds, deep learning and decision tree approaches. It builds on three important blocks: (a) a hierarchical space partition over the indoor scene to construct the decision tree; (b) a neural routing function, implemented as a deep classification network, employed for better 3D scene understanding; and (c) an outlier rejection module used to filter out dynamic points during the hierarchical routing process. Our proposed algorithm is evaluated on the RIO-10 benchmark developed for camera relocalization in dynamic indoor environments. It achieves robust neural routing through space partitions and outperforms the state-of-the-art approaches by around 30% on camera pose accuracy, while running comparably fast for evaluation.