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A curated list of Object SLAM papers and resources
| Date | Stars |
|---|---|
| 2026-07-24 | 300 |
| 2026-07-25 | 300 |
| 2026-07-28 | 300 |
| 2026-07-30 | 300 |
| 2026-08-06 | 300 |
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# Awesome Object SLAM [](https://github.com/sindresorhus/awesome) A curated list of Object SLAM papers and resources, inspired by [awesome-implicit-representations](https://github.com/vsitzmann/awesome-implicit-representations). ## Disclaimer This list *does not aim to be exhaustive*. In this list, we consider papers that **jointly** optimize robot (camera) and object states, where object states typically include object poses and object shape parameters. For more general SLAM papers, please refer to [awesome-visual-SLAM](https://github.com/tzutalin/awesome-visual-slam) and [Awesome-SLAM](https://github.com/SilenceOverflow/Awesome-SLAM). This repo is mainitained by [Ziqi Lu](https://github.com/520xyxyzq) and [Akash Sharma](https://github.com/akashsharma02). You are very welcome to contribute to this repo. If you spot anything wrong or missing, please feel free to [submit a pull request](https://github.com/520xyxyzq/awesome-object-SLAM/pulls) or contact the maintainers. ## Table of Contents - [What is Object SLAM](#what-is-object-slam?) - [Papers](#papers) - [Parametric Object Representation](#parametric-object-representation-cubesquadrics6dof-poseetc) - [Field Object Representation](#field-object-representation-neural-fieldsdense-gridsetc) - [Inference Methods for Object SLAM](#inference-methods-for-object-slam) - [Reviews](#reviews) - [Resources](#resources) - [Datasets](#datasets) ## What is Object SLAM? Object SLAM, loosely speaking tackles the problem of Simultaneous Localisation and Mapping (SLAM) by building a _3D object-level global environment map from local observations_. To build such a map of the environment, object detection, pose estimation and instance segmentation networks are typically used as virtual sensors in a sensor fusion framework. Representing the 3D map with objects is interesting as it is easy to ascribe semantics to the landmarks to perform higher-level tasks such as object manipulation, motion and task planning, etc. It compresses the map by focusing compute and memory for meaningful regions, and map abstraction is also useful for other tasks such as distributed map building. ## Papers ### Parametric Object Representation (Cubes/Quadrics/6DoF Pose/etc.) - #### 2024 - DynaQuadric: Dynamic Quadric SLAM for Quadric Initialization, Mapping, and Tracking. [\[PDF\]](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10591477) - Learning from Feedback: Semantic Enhancement for Object SLAM Using Foundation Models. [\[PDF\]](https://arxiv.org/pdf/2411.06752) - Multi-Robot Object SLAM using Distributed Variational Inference. [\[PDF\]](https://arxiv.org/pdf/2404.18331) [\[Code\]](https://github.com/intrepidChw/distributed_msckf) - VOOM: Robust Visual Object Odometry and Mapping using Hierarchical Landmarks. [\[PDF\]](https://arxiv.org/pdf/2402.13609.pdf) [\[Code\]](https://github.com/yutongwangBIT/VOOM) - #### 2023 - An Object SLAM Framework for Association, Mapping, and High-Level Tasks. [\[PDF\]](https://arxiv.org/pdf/2305.07299.pdf) - BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects. [\[PDF\]](https://arxiv.org/abs/2303.14158) [\[Code\]](https://github.com/NVlabs/BundleSDF) [\[Video\]](https://www.youtube.com/watch?v=5PymzKbKv8w) - Object-based SLAM utilizing unambiguous pose parameters considering general symmetry types. [\[PDF\]](https://arxiv.org/pdf/2303.07872.pdf) [\[Video\]](https://www.youtube.com/watch?v=aVc4x3hsVo4) - ObVi-SLAM: Long-Term Object-Visual SLAM. [\[PDF\]](https://arxiv.org/pdf/2309.15268.pdf) [\[Code\]](https://github.com/ut-amrl/ObVi-SLAM) [\[Video\]](https://youtu.be/quJOgnEdaZ0) - UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling. [\[PDF\]](https://arxiv.org/pdf/2309.17036.pdf) - #### 2022 - LayoutSLAM: Object Layout based Simultaneous Localization and Mapping
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:7316726e22357c0c, topic:slam, readme:manipulation, name:slam