mlsanityData to 14 Oct 2026

Understanding while Exploring: Semantics-driven Active Mapping

arXiv 2506.00225 ↗First posted 30 May 2025cs.RO cs.CVcited by 5

Not on the map. Why?

Abstract (arXiv)

Effective robotic autonomy in unknown environments demands proactive exploration and precise understanding of both geometry and semantics. In this paper, we propose ActiveSGM, an active semantic mapping framework designed to predict the informativeness of potential observations before execution. Built upon a 3D Gaussian Splatting (3DGS) mapping backbone, our approach employs semantic and geometric uncertainty quantification, coupled with a sparse semantic representation, to guide exploration. By enabling robots to strategically select the most beneficial viewpoints, ActiveSGM efficiently enhances mapping completeness, accuracy, and robustness to noisy semantic data, ultimately supporting more adaptive scene exploration. Our experiments on the Replica and Matterport3D datasets highlight the effectiveness of ActiveSGM in active semantic mapping tasks.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 79 of its 103 references that are in the map. First posted on arXiv 30 May 2025.

Builds on

79 of 103 references.

References · 79

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  3. 2017Mask R-CNNcited by 7,277
  4. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,968
  5. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  6. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,351
  7. 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,376
  8. 2019Habitat: A Platform for Embodied AI Researchcited by 1,191
  9. 2022Reproducible scaling laws for contrastive language-image learningcited by 1,173
  10. 2019The Replica Dataset: A Digital Replica of Indoor Spacescited by 904
  11. 2020ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAMcited by 878
  12. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 600
38 more
  1. 2021NICE-SLAM: Neural Implicit Scalable Encoding for SLAMcited by 589
  2. 2021Neural Fields in Visual Computing and Beyondcited by 540
  3. 2021iMAP: Implicit Mapping and Positioning in Real-Timecited by 476
  4. 2023Gaussian Splatting SLAMcited by 415
  5. 2023LangSplat: 3D Language Gaussian Splattingcited by 415
  6. 2016Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Agecited by 411
  7. 2023SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAMcited by 388
  8. 2021Advances in Neural Renderingcited by 365
  9. 2022OneFormer: One Transformer to Rule Universal Image Segmentationcited by 328
  10. 2023GS-SLAM: Dense Visual SLAM with 3D Gaussian Splattingcited by 278
  11. 2019Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mappingcited by 184
  12. 2023Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAMcited by 184
  13. 2023NICER-SLAM: Neural Implicit Scene Encoding for RGB SLAMcited by 164
  14. 2022ESLAM: Efficient Dense SLAM System Based on Hybrid Representation of Signed Distance Fieldscited by 158
  15. 2021Vision-Only Robot Navigation in a Neural Radiance Worldcited by 155
  16. 2023Gaussian-SLAM: Photo-realistic Dense SLAM with Gaussian Splattingcited by 154
  17. 2022PONI: Potential Functions for ObjectGoal Navigation with Interaction-free Learningcited by 150
  18. 2024HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splattingcited by 142
  19. 2023Photo-SLAM: Real-time Simultaneous Localization and Photorealistic Mapping for Monocular, Stereo, and RGB-D Camerascited by 141
  20. 2016SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networkscited by 135
  21. 2023GO-SLAM: Global Optimization for Consistent 3D Instant Reconstructioncited by 133
  22. 2022ActiveNeRF: Learning where to See with Uncertainty Estimationcited by 127
  23. 2020Occupancy Anticipation for Efficient Exploration and Navigationcited by 106
  24. 2022Navigating to Objects in the Real Worldcited by 106
  25. 20243D Gaussian as a New Era: A Surveycited by 104
  26. 2018Fusion++: Volumetric Object-Level SLAMcited by 98
  27. 2019PanopticFusion: Online Volumetric Semantic Mapping at the Level of Stuff and Thingscited by 98
  28. 2024SGS-SLAM: Semantic Gaussian Splatting For Neural Dense SLAMcited by 87
  29. 2022Orbeez-SLAM: A Real-time Monocular Visual SLAM with ORB Features and NeRF-realized Mappingcited by 79
  30. 20243D Gaussian Splatting: Survey, Technologies, Challenges, and Opportunitiescited by 78
  31. 2024How NeRFs and 3D Gaussian Splatting are Reshaping SLAM: a Surveycited by 72
  32. 2022A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontierscited by 66
  33. 2023SNI-SLAM: Semantic Neural Implicit SLAMcited by 65
  34. 2023PLGSLAM: Progressive Neural Scene Represenation with Local to Global Bundle Adjustmentcited by 63
  35. 2019Visual Odometry Revisited: What Should Be Learnt?cited by 57
  36. 2022NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representationscited by 55
  37. 2022Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fieldscited by 54
  38. 2021Learning to Map for Active Semantic Goal Navigationcited by 50

50 most cited of 79 All 79 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 5.

5 papers.

  1. 2026MAGICIAN: Efficient Long-Term Planning with Imagined Gaussians for Active Mappingcited by 5
  2. 2026B3-Seg: Camera-Free, Training-Free 3DGS Segmentation via Analytic EIG and Beta-Bernoulli Bayesian Updatescited by 2
  3. 2026Fixed External Cameras as Common Prior Maps for Active 3D Scene Graph Generationcited by 0
  4. 2026RGB-only Active 3D Scene Graph Generation for Indoor Mobile Robotscited by 0
  5. 2026Multi-Scale Semantic Mapping in Urban Environments via Observation Calibration and Policy Dependence Regularizationcited by 0