# EAO-SLAM: Monocular Semi-Dense Object SLAM Based on Ensemble Data Association

arXiv: https://arxiv.org/abs/2004.12730 · HTML: https://mlsanity.com/paper/2004.12730/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Apr 2020.

## Built on by (most cited first, 24 of 24)

- [Incremental 3D Semantic Scene Graph Prediction from RGB Sequences](https://mlsanity.com/paper/2305.02743/) (2023)
- [Deep Learning for Camera Calibration and Beyond: A Survey](https://mlsanity.com/paper/2303.10559/) (2023)
- [OA-SLAM: Leveraging Objects for Camera Relocalization in Visual SLAM](https://mlsanity.com/paper/2209.08338/) (2022)
- [An Object SLAM Framework for Association, Mapping, and High-Level Tasks](https://mlsanity.com/paper/2305.07299/) (2023)
- [Stereo CenterNet based 3D Object Detection for Autonomous Driving](https://mlsanity.com/paper/2103.11071/) (2021)
- [ELLIPSDF: Joint Object Pose and Shape Optimization with a Bi-level Ellipsoid and Signed Distance Function Description](https://mlsanity.com/paper/2108.00355/) (2021)
- [Applications of Spiking Neural Networks in Visual Place Recognition](https://mlsanity.com/paper/2311.13186/) (2023)
- [ObVi-SLAM: Long-Term Object-Visual SLAM](https://mlsanity.com/paper/2309.15268/) (2023)
- [Semantic Visual Simultaneous Localization and Mapping: A Survey](https://mlsanity.com/paper/2209.06428/) (2022)
- [Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry](https://mlsanity.com/paper/2101.05995/) (2021)
- [VOOM: Robust Visual Object Odometry and Mapping using Hierarchical Landmarks](https://mlsanity.com/paper/2402.13609/) (2024)
- [Image Patch-Matching with Graph-Based Learning in Street Scenes](https://mlsanity.com/paper/2311.04617/) (2023)
- [Semantic Enhancement for Object SLAM with Heterogeneous Multimodal Large Language Model Agents](https://mlsanity.com/paper/2411.06752/) (2024)
- [Active 6D Pose Estimation for Textureless Objects using Multi-View RGB Frames](https://mlsanity.com/paper/2503.03726/) (2025)
- [TransPoser: Transformer as an Optimizer for Joint Object Shape and Pose Estimation](https://mlsanity.com/paper/2303.13477/) (2023)
- [SemanticTopoLoop: Semantic Loop Closure With 3D Topological Graph Based on Quadric-Level Object Map](https://mlsanity.com/paper/2311.02831/) (2023)
- [PAS-SLAM: A Visual SLAM System for Planar Ambiguous Scenes](https://mlsanity.com/paper/2402.06131/) (2024)
- [Accurate and Robust Object-oriented SLAM with 3D Quadric Landmark Construction in Outdoor Environment](https://mlsanity.com/paper/2110.08977/) (2021)
- [Loop Closure Detection Based on Object-level Spatial Layout and Semantic Consistency](https://mlsanity.com/paper/2304.05146/) (2023)
- [UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling](https://mlsanity.com/paper/2309.17036/) (2023)
- [MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization](https://mlsanity.com/paper/2512.03522/) (2025)
- [Self-supervised Learning of 3D Object Understanding by Data Association and Landmark Estimation for Image Sequence](https://mlsanity.com/paper/2104.07077/) (2021)
- [3 Dimensional Dense Reconstruction: A Review of Algorithms and Dataset](https://mlsanity.com/paper/2304.09371/) (2023)
- [Convex Hull-based Algebraic Constraint for Visual Quadric SLAM](https://mlsanity.com/paper/2503.01254/) (2025)

## Abstract (arXiv)

Object-level data association and pose estimation play a fundamental role in semantic SLAM, which remain unsolved due to the lack of robust and accurate algorithms. In this work, we propose an ensemble data associate strategy for integrating the parametric and nonparametric statistic tests. By exploiting the nature of different statistics, our method can effectively aggregate the information of different measurements, and thus significantly improve the robustness and accuracy of data association. We then present an accurate object pose estimation framework, in which an outliers-robust centroid and scale estimation algorithm and an object pose initialization algorithm are developed to help improve the optimality of pose estimation results. Furthermore, we build a SLAM system that can generate semi-dense or lightweight object-oriented maps with a monocular camera. Extensive experiments are conducted on three publicly available datasets and a real scenario. The results show that our approach significantly outperforms state-of-the-art techniques in accuracy and robustness. The source code is available on: https://github.com/yanmin-wu/EAO-SLAM.