mlsanityData to 14 Oct 2026

S3LAM: Structured Scene SLAM

arXiv 2109.07339 ↗First posted 15 Sep 2021cs.RO cs.CVcited by 5

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Abstract (arXiv)

We propose a new SLAM system that uses the semantic segmentation of objects and structures in the scene. Semantic information is relevant as it contains high level information which may make SLAM more accurate and robust. Our contribution is twofold: i) A new SLAM system based on ORB-SLAM2 that creates a semantic map made of clusters of points corresponding to objects instances and structures in the scene. ii) A modification of the classical Bundle Adjustment formulation to constrain each cluster using geometrical priors, which improves both camera localization and reconstruction and enables a better understanding of the scene. We evaluate our approach on sequences from several public datasets and show that it improves camera pose estimation with respect to state of the art.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 29 of its 57 references that are in the map. First posted on arXiv 15 Sep 2021.

Builds on

29 of 57 references.

References · 29

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2017Mask R-CNNcited by 7,277
  3. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  4. 2015ORB-SLAM: a Versatile and Accurate Monocular SLAM Systemcited by 988
  5. 2016ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Camerascited by 806
  6. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
  7. 2019Panoptic Feature Pyramid Networkscited by 645
  8. 2016Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Agecited by 411
  9. 2017BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depthcited by 225
  10. 2019Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mappingcited by 184
  11. 2017CNN-SLAM: Real-time dense monocular SLAM with learned depth predictioncited by 152
  12. 2016SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networkscited by 135
17 more
  1. 2018DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenescited by 134
  2. 2018CubeSLAM: Monocular 3D Object SLAMcited by 102
  3. 2018MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objectscited by 95
  4. 2018DS-SLAM: A Semantic Visual SLAM towards Dynamic Environmentscited by 91
  5. 2018QuadricSLAM: Dual Quadrics from Object Detections as Landmarks in Object-oriented SLAMcited by 86
  6. 2017Semantic Visual Localizationcited by 54
  7. 2020DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAMcited by 47
  8. 2016Meaningful Maps With Object-Oriented Semantic Mappingcited by 31
  9. 2018Monocular Object and Plane SLAM in Structured Environmentscited by 23
  10. 2019Is This The Right Place? Geometric-Semantic Pose Verification for Indoor Visual Localizationcited by 18
  11. 2017Pop-up SLAM: Semantic Monocular Plane SLAM for Low-texture Environmentscited by 17
  12. 2018Structure Aware SLAM using Quadrics and Planescited by 17
  13. 2018Real-Time Monocular Object-Model Aware Sparse SLAMcited by 17
  14. 2020ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundingscited by 17
  15. 2015Real-time Monocular Object SLAMcited by 7
  16. 2020L6DNet: Light 6 DoF Network for Robust and Precise Object Pose Estimation with Small Datasetscited by 5
  17. 2016Semi-Dense 3D Semantic Mapping from Monocular SLAMcited by 4

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Citing papers per year: 2022: 5.

5 papers.