mlsanityData to 7 Oct 2026

ActiveRMAP: Radiance Field for Active Mapping And Planning

arXiv 2211.12656 ↗First posted 23 Nov 2022cs.CV cs.ROcited by 29

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Abstract (arXiv)

A high-quality 3D reconstruction of a scene from a collection of 2D images can be achieved through offline/online mapping methods. In this paper, we explore active mapping from the perspective of implicit representations, which have recently produced compelling results in a variety of applications. One of the most popular implicit representations - Neural Radiance Field (NeRF), first demonstrated photorealistic rendering results using multi-layer perceptrons, with promising offline 3D reconstruction as a by-product of the radiance field. More recently, researchers also applied this implicit representation for online reconstruction and localization (i.e. implicit SLAM systems). However, the study on using implicit representation for active vision tasks is still very limited. In this paper, we are particularly interested in applying the neural radiance field for active mapping and planning problems, which are closely coupled tasks in an active system. We, for the first time, present an RGB-only active vision framework using radiance field representation for active 3D reconstruction and planning in an online manner. Specifically, we formulate this joint task as an iterative dual-stage optimization problem, where we alternatively optimize for the radiance field representation and path planning. Experimental results suggest that the proposed method achieves competitive results compared to other offline methods and outperforms active reconstruction methods using NeRFs.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 34 of its 71 references that are in the map. First posted on arXiv 23 Nov 2022.

Builds on

34 of 71 references.

References · 34

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
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  3. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  4. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  5. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
  6. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,607
  7. 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,574
  8. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,459
  9. 2022TensoRF: Tensorial Radiance Fieldscited by 1,275
  10. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 961
  11. 2020Neural Sparse Voxel Fieldscited by 959
  12. 2020NeRF++: Analyzing and Improving Neural Radiance Fieldscited by 857
22 more
  1. 2020GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fieldscited by 784
  2. 2018MVSNet: Depth Inference for Unstructured Multi-view Stereocited by 780
  3. 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 732
  4. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 688
  5. 2021KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPscited by 672
  6. 2021BARF: Bundle-Adjusting Neural Radiance Fieldscited by 641
  7. 2021FastNeRF: High-Fidelity Neural Rendering at 200FPScited by 510
  8. 2021iMAP: Implicit Mapping and Positioning in Real-Timecited by 476
  9. 2016Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Agecited by 405
  10. 2021Neural RGB-D Surface Reconstructioncited by 312
  11. 2021NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Videocited by 241
  12. 2021Vision-Only Robot Navigation in a Neural Radiance Worldcited by 153
  13. 2022ActiveNeRF: Learning where to See with Uncertainty Estimationcited by 124
  14. 2022GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimationcited by 86
  15. 2022A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontierscited by 62
  16. 2019Visual Odometry Revisited: What Should Be Learnt?cited by 57
  17. 2022NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representationscited by 54
  18. 2022Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fieldscited by 53
  19. 2020Next-Best View Policy for 3D Reconstructioncited by 35
  20. 2021NeuLF: Efficient Novel View Synthesis with Neural 4D Light Fieldcited by 33
  21. 2022PlaneMVS: 3D Plane Reconstruction from Multi-View Stereocited by 29
  22. 2022BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusioncited by 29

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 9; 2025: 11; 2026: 5.

29 papers.

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  1. 2023Bayes' Rays: Uncertainty Quantification for Neural Radiance Fieldscited by 90
  2. 2024GenNBV: Generalizable Next-Best-View Policy for Active 3D Reconstructioncited by 39
  3. 2024NARUTO: Neural Active Reconstruction from Uncertain Target Observationscited by 27
  4. 2024Neural Visibility Field for Uncertainty-Driven Active Mappingcited by 25
  5. 2023Improving NeRF Quality by Progressive Camera Placement for Unrestricted Navigation in Complex Environmentscited by 19
  6. 2025ActiveGAMER: Active GAussian Mapping through Efficient Renderingcited by 19
  7. 2023Estimating 3D Uncertainty Field: Quantifying Uncertainty for Neural Radiance Fieldscited by 14
  8. 2025NextBestPath: Efficient 3D Mapping of Unseen Environmentscited by 13
  9. 2023AutoNeRF: Training Implicit Scene Representations with Autonomous Agentscited by 10
  10. 2025GLEAM: Learning Generalizable Exploration Policy for Active Mapping in Complex 3D Indoor Scenescited by 10
  11. 2024Multimodal LLM Guided Exploration and Active Mapping using Fisher Informationcited by 9
  12. 2024Invertible Neural Warp for NeRFcited by 5
17 more
  1. 2025Understanding while Exploring: Semantics-driven Active Mappingcited by 5
  2. 2025Uncertainty Matters in Dynamic Gaussian Splatting for Monocular 4D Reconstructioncited by 5
  3. 2025Peering into the Unknown: Active View Selection with Neural Uncertainty Maps for 3D Reconstructioncited by 4
  4. 2025WarpRF: Multi-View Consistency for Training-Free Uncertainty Quantification and Applications in Radiance Fieldscited by 2
  5. 2024STAIR: Semantic-Targeted Active Implicit Reconstructioncited by 1
  6. 2024GURecon: Learning Detailed 3D Geometric Uncertainties for Neural Surface Reconstructioncited by 1
  7. 2025BayesSDF: Surface-Based Laplacian Uncertainty Estimation for 3D Geometry with Neural Signed Distance Fieldscited by 1
  8. 2025Hestia: Voxel-Face-Aware Hierarchical Next-Best-View Acquisition for Efficient 3D Reconstructioncited by 1
  9. 2026Rethinking Pose Refinement in 3D Gaussian Splatting under Pose Prior and Geometric Uncertaintycited by 1
  10. 2024Surface-Based Visibility-Guided Uncertainty for Continuous Active 3D Neural Reconstructioncited by 0
  11. 2024RIGI: Rectifying Image-to-3D Generation Inconsistency via Uncertainty-aware Learningcited by 0
  12. 2025Data Augmentation for NeRFs in the Low Data Limitcited by 0
  13. 2025Camera Splatting for Continuous View Optimizationcited by 0
  14. 2026ScanDP: Generalizable 3D Scanning with Diffusion Policycited by 0
  15. 2026CASA-SDF: Curriculum-Aware Spatial Adaptation with Curvature-Guided Density for Neural Implicit Surface Reconstructioncited by 0
  16. 2026FillGS: Filling Observation Gaps in 4D Gaussian Splatting via Viewpoint-Time Selection and Generative Refinementcited by 0
  17. 2026ActiveLang: Active Open-Vocabulary 3D Mapping with Semantic-Uncertainty-Guided Explorationcited by 0