Awesome-Semantic-Object-SLAM

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Awesome-Semantic-Object-SLAM

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🚀Collection of Papers with Code: Representation, Association and Semantic Scene Matching for Object-Oriented SLAM Using Monocular, RGB-D and LiDAR

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# Awesome Semantic-Object-SLAM [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)

This repository considers papers that optimize robot and object states based on Monocular, RGB-D, and LiDAR, as well as papers that perform loop closure detection through semantic scene matching.  
🔥This repository is still under construction and will continue to be updated!🔥

## Contents

- [Papers](#papers)
  - [Object SLAM & Parameterization](#object-slam--parameterization)
  - [Semantic Scene Matching for Loop Closing](#semantic-scene-matching-for-loop-closing)
- [Resources](#resources)
  - [Datasets](#datasets)

## News

**`24.08.01`**  First commit!

## Papers

### Object SLAM & Parameterization

| Year | Venue | Paper Title | Repository |
|:----:|:-----:|-------------|------------|
| `2024` | `arXiv` | [SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation](https://arxiv.org/pdf/2406.17249) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/XuRobotics/slide-slam) |
| `2024` | `arXiv` | [Multi-Robot Object SLAM using Distributed Variational Inference](https://arxiv.org/pdf/2404.18331) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/intrepidChw/distributed_msckf) |
| `2024` | `ICRA` | [VOOM: Robust Visual Object Odometry and Mapping using Hierarchical Landmarks](https://arxiv.org/pdf/2402.13609.pdf) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/yutongwangBIT/VOOM) |
| `2024` | `RA-L` | [ObVi-SLAM: Long-Term Object-Visual SLAM](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10423794) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/ut-amrl/ObVi-SLAM) |
| `2023` | `T-RO` | [An Object SLAM Framework for Association, Mapping, and High-Level Tasks](https://arxiv.org/pdf/2305.07299.pdf) | N/A |
| `2023` | `T-ITS` | [Object SLAM With Robust Quadric Initialization and Mapping for Dynamic Outdoors](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10149129) | N/A |
| `2023` | `RA-L` | [QISO-SLAM: Object-Oriented SLAM Using Dual Quadrics as Landmarks Based on Instance Segmentation](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10056983) | N/A |
| `2023` | `JIRS` [1] | [SQ-SLAM: Monocular Semantic SLAM Based on Superquadric Object Representation](https://arxiv.org/pdf/2209.10817.pdf) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/XiaoHan-Git/SQ-SLAM) |
| `2023` | `ICRA` | [Object-based SLAM utilizing unambiguous pose parameters considering general symmetry types](https://arxiv.org/pdf/2303.07872.pdf) | N/A |
| `2023` | `arXiv` | [UniQuadric: A SLAM Backend for Unknown Rigid Object 3D Tracking and Light-Weight Modeling](https://arxiv.org/pdf/2309.17036.pdf) | N/A |
| `2022` | `ICRA` | [Unified Representation of Geometric Primitives for Graph-SLAM Optimization Using Decomposed Quadrics](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9812162) | N/A |
| `2022` | `IROS` | [LayoutSLAM: Object Layout based Simultaneous Localization and Mapping for Reducing Object Map Distortion](https://ieeexplore.ieee.org/abstract/document/9981492) | N/A |
| `2022` | `ISMAR`  | [OA-SLAM: Leveraging Objects for Camera Relocalization in Visual SLAM](https://arxiv.org/pdf/2209.08338.pdf) | [![Code](https://img.shields.io/badge/Gitlab-Repository-blue)](https://gitlab.inria.fr/tangram/oa-slam) |
| `2022` | `RA-L` | [SO-SLAM: Semantic Object SLAM with Scale Proportional and Symmetrical Texture Constraints](https://arxiv.org/pdf/2109.04884.pdf) | [![Code1](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/XunshanMan/SoSLAM) [![Code2](https://img.shields.io/badge/Github-Repository-red)](https://github.com/MRHan-426/SOSLAM)|
| `2022` | `CVPR` | [Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation](https://openaccess.thecvf.com/content/CVPR2022/papers/Merrill_Symmetry_and_Uncertainty-Aware_Object_SLAM_for_6DoF_Object_Pose_Estimation_CVPR_2022_paper.pdf) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/rpng/suo_slam) |
| `2022` | `RA-L` | [Accurate and Robust Object SLAM With 3D Quadric Landmark Reconstruction in Outdoors](https://arxiv.org/pdf/2110.08977.pdf)  | N/A |
| `2021` | `IROS` | [LiDAR-Based Object-Level SLAM for Autonomous Vehicles](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9636299) | N/A |
| `2021` | `ICCV` | [ODAM: Object Detection, Association, and Mapping using Posed RGB Video](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9710968) | [![Code](https://img.shields.io/badge/Gitlab-Repository-blue)](https://github.com/likojack/odam)|
| `2021` | `RA-L` | [DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAM](https://arxiv.org/pdf/2010.07820.pdf) | N/A |
| `2021` | `arXiv` | [Superquadric Object Representation for Optimization-based Semantic SLAM](https://arxiv.org/pdf/2109.09627) | N/A |
| `2020` | `IROS` | [EAO-SLAM: Monocular Semi-Dense Object SLAM Based on Ensemble Data Association](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9341757) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/yanmin-wu/EAO-SLAM) |
| `2019` | `ICRA` | [Robust Object-based SLAM for High-speed Autonomous Navigation](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8794344) | N/A |
| `2019` | `RA-L` | [Monocular Object and Plane SLAM in Structured Environments](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8744612) | N/A |
| `2019` | `T-RO` | [CubeSLAM: Monocular 3D Object SLAM](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8708251) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/shichaoy/cube_slam) |
| `2019` | `RA-L` | [QuadricSLAM: Dual Quadrics From Object Detections as Landmarks in Object-Oriented SLAM](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8440105) | [![Code1](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/qcr/quadricslam)  [![Code2](https://img.shields.io/badge/Github-Repository-purple)](https://github.com/qcr/gtsam-quadrics)|
| `2018` | `ACCV` | [Structure Aware SLAM using Quadrics and Planes](https://arxiv.org/pdf/1804.09111) | N/A |

[1]: JIRS = Journal of Intelligent & Robotic Systems 
[<a href="#contents">back to table</a>]

### Semantic Scene & Correspondence Matching

| Year | Venue | Paper Title | Repository |
|:----:|:----:|-------------|------------|
| `2024` | `RA-L` | [CLIP-Clique: Graph-Based Correspondence  Matching Augmented by Vision Language  Models for Object-Based  Global Localization](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705086)| N/A |
| `2024` | `RA-L` | [SemanticTopoLoop: Semantic Loop Closure With 3D Topological Graph Based on Quadric-Level Object Map](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10460989) | N/A |
| `2023` | `arXiv` | [Loop Closure Detection Based on Object-level Spatial Layout and Semantic Consistency](https://arxiv.org/pdf/2304.05146) | N/A |
| `2022` | `RA-L` | [Towards Accurate Loop Closure Detection in Semantic SLAM With 3D Semantic Covisibility Graphs](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9691853) | N/A |
| `2022` | `CASE` | [Object-based Loop Closure with Directional Histogram Descriptor](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9926687) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/benchun123/object-based-loop-closure?tab=readme-ov-file) |
| `2021` | `JVCIR` [2] | [Semantic loop closure detection based on graph matching in multi-objects scenes](https://www.sciencedirect.com/science/article/pii/S1047320321000389) | N/A |
| `2021` | `RA-L` | [Topology Aware Object-Level Semantic Mapping Towards More Robust Loop Closure](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9484819) | N/A |
| `2021` | `RA-L` | [Semantic histogram based graph matching for real-time multi-robot global localization in large scale environment](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9353207) | [![Code](https://img.shields.io/badge/Github-Repository-blue)](https://github.com/gxytcrc/semantic-histogram-based-global-localization) |
| `2019` | `ICRA` | [Global localization with objectlevel semantics and topology](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8794475) | N/A |
| `2019` | `ICRA` | [Semantic Mapping for View-Invariant Relocalization](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8793624) | N/A |
| `2017` | `RA-L` | [X-View: Graph-Based Semantic Multi-View Localization](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8281068) | N/A |

[2]: JVCIR = Journal of Visual Communication and Image Representation
[<a href="#contents">back to table</a>]

----------------------
## Resources

### Datasets

| Dataset Name | Description | Link |
|--------------------|-------------------------------------------------------------------------------------------------------|------------------------------------------------------------|
| KITTI | A well-known dataset for autonomous driving research, offering stereo and LiDAR data for tasks like object detection, tracking, and SLAM. | [KITTI](https://www.cvlibs.net/datasets/kitti/index.php) |
| SemanticKITTI | A large-scale dataset providing semantic segmentation labels for LiDAR point clouds, based on the KITTI Odometry Benchmark, suitable for autonomous driving applications. | [SemanticKITTI](https://www.semantic-kitti.org/) |
| Replica | A highly detailed and realistic dataset of 18 indoor environments, providing photorealistic textures and semantic annotations for 3D research. | [Replica](https://github.com/facebookresearch/Replica-Dataset) |
| TUM | A dataset for evaluating RGB-D SLAM systems, containing benchmark sequences recorded with a Microsoft Kinect camera. | [TUM](https://vision.in.tum.de/data/datasets/rgbd-dataset/download) |
| Matterport3D | A large dataset of indoor RGB-D images with 3D meshes and semantic annotations, used for developing scene understanding algorithms. | [Matterport3D](https://niessner.github.io/Matterport/) |
| SUN RGB-D | A dataset containing RGB-D images from various sensors, annotated with 3D bounding boxes for object detection and scene understanding research. | [SUN RGB-D](https://rgbd.cs.princeton.edu/) |
| Microsoft-RGBD | A dataset featuring RGB-D sequences captured in various indoor environments, used for scene understanding and 3D reconstruction tasks. | [Microsoft-RGBD](https://www.microsoft.com/en-us/research/project/rgb-d-dataset-7-scenes/) |
| NYU Depth v2 | An RGB-D dataset collected with a Kinect sensor, providing labeled depth maps and semantic annotations for indoor scenes. | [NYU Depth v2](https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html) |
| Redwood-OS | A collection of RGB-D sequences designed for evaluating 3D reconstruction algorithms, with a focus on object and scene scanning. | [Redwood-OS](http://redwood-data.org/3dscan/) |
| RGBD Scenes v1 | A dataset with RGB-D video sequences for studying 3D object recognition and scene understanding, featuring cluttered indoor environments. | [RGBD Scenes v1](https://rgbd-dataset.cs.washington.edu/) |
| RGBD Scenes v2 | An extended version of RGBD Scenes v1, providing additional objects and sequences for more complex scene analysis. | [RGBD Scenes v2](https://rgbd-dataset.cs.washington.edu/dataset/rgbd-scenes-v2/) |
| ICL-NUIM | A synthetic RGB-D dataset for benchmarking SLAM and visual odometry algorithms, featuring photo-realistic scenes. | [ICL-NUIM](https://www.doc.ic.ac.uk/~ahanda/VaFRIC/iclnuim.html) |
| ScanNet | A richly annotated dataset with RGB-D video sequences of indoor environments, aimed at advancing 3D scene understanding and reconstruction. | [ScanNet](http://www.scan-net.org/) |
| YCB-Video | A dataset for benchmarking 6-DoF object pose estimation in video, including real and synthetic sequences of household objects. | [YCB-Video](https://rse-lab.cs.washington.edu/projects/posecnn/) |
| ApolloScape | A comprehensive dataset for autonomous driving, providing annotated 2D/3D images and point clouds from real-world traffic scenarios. | [ApolloScape](http://apolloscape.auto/) |
| Cityscapes | A large-scale dataset for semantic urban scene understanding, featuring pixel-level annotations for various urban street scenes. | [Cityscapes](https://www.cityscapes-dataset.com/) |
[<a href="#contents">back to table</a>]

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