mlsanityData to 7 Oct 2026

Auto3R: Automated 3D Reconstruction and Scanning via Data-driven Uncertainty Quantification

arXiv 2512.04528 ↗First posted 4 Dec 2025cs.CVcited by 4

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Abstract (arXiv)

Traditional high-quality 3D scanning and reconstruction typically relies on human labor to plan the scanning procedure. With the rapid development of embodied systems such as drones and robots, there is a growing demand of performing accurate 3D scanning and reconstruction in an fully automated manner. We introduce Auto3R, a data-driven uncertainty quantification model that is designed to automate the 3D scanning and reconstruction of scenes and objects, including objects with non-lambertian and specular materials. Specifically, in a process of iterative 3D reconstruction and scanning, Auto3R can make efficient and accurate prediction of uncertainty distribution over potential scanning viewpoints, without knowing the ground truth geometry and appearance. Through extensive experiments, Auto3R achieves superior performance that outperforms the state-of-the-art methods by a large margin. We also deploy Auto3R on a robot arm equipped with a camera and demonstrate that Auto3R can be used to effectively digitize real-world 3D objects and delivers ready-to-use and photorealistic digital assets. Our homepage: https://tomatoma00.github.io/auto3r.github.io .

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 33 of its 49 references that are in the map. First posted on arXiv 4 Dec 2025.

Builds on

33 of 49 references.

References · 33

  1. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  2. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
  3. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
  4. 2021MUSIQ: Multi-scale Image Quality Transformercited by 1,058
  5. 2022MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessmentcited by 514
  6. 2023TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessmentcited by 220
  7. 2021No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistencycited by 165
  8. 2022ActiveNeRF: Learning where to See with Uncertainty Estimationcited by 124
  9. 2021Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimationcited by 116
  10. 2022Map-free Visual Relocalization: Metric Pose Relative to a Single Imagecited by 112
  11. 2023Bayes' Rays: Uncertainty Quantification for Neural Radiance Fieldscited by 90
  12. 2023GIR: 3D Gaussian Inverse Rendering for Relightable Scene Factorizationcited by 86
21 more
  1. 2024PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splattingcited by 85
  2. 2021Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representationscited by 80
  3. 2022Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fieldscited by 58
  4. 2022NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representationscited by 54
  5. 2023NeU-NBV: Next Best View Planning Using Uncertainty Estimation in Image-Based Neural Renderingcited by 53
  6. 2024GenNBV: Generalizable Next-Best-View Policy for Active 3D Reconstructioncited by 39
  7. 2024ActiveGS: Active Scene Reconstruction Using Gaussian Splattingcited by 34
  8. 2024ActiveSplat: High-Fidelity Scene Reconstruction through Active Gaussian Splattingcited by 32
  9. 2024Material Anything: Generating Materials for Any 3D Object via Diffusioncited by 31
  10. 2023Active Implicit Object Reconstruction using Uncertainty-guided Next-Best-View Optimizationcited by 27
  11. 2024Neural Visibility Field for Uncertainty-Driven Active Mappingcited by 25
  12. 2024Modeling uncertainty for Gaussian Splattingcited by 17
  13. 2025GauSS-MI: Gaussian Splatting Shannon Mutual Information for Active 3D Reconstructioncited by 15
  14. 2024NeRF Director: Revisiting View Selection in Neural Volume Renderingcited by 14
  15. 2024Manifold Sampling for Differentiable Uncertainty in Radiance Fieldscited by 11
  16. 2022The Surface Edge Explorer (SEE): A measurement-direct approach to next best view planningcited by 9
  17. 2023Multi-view 3D Object Reconstruction and Uncertainty Modelling with Neural Shape Priorcited by 9
  18. 2016UAV-based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Predictioncited by 6
  19. 2018Surface Edge Explorer (SEE): Planning Next Best Views Directly from 3D Observationscited by 5
  20. 2025Peering into the Unknown: Active View Selection with Neural Uncertainty Maps for 3D Reconstructioncited by 4
  21. 2020Proactive Estimation of Occlusions and Scene Coverage for Planning Next Best Views in an Unstructured Representationcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026OA-NBV: Occlusion-Aware Next-Best-View Planning for Human-Centered Active Perception on Mobile Robotscited by 2
  2. 2026GO-PRE: Goal-Oriented Next-Best-View Selection via Predictive Rendering Entropy for Active 3D Reconstructioncited by 1
  3. 20262D GauSS-MI: Efficient Active Scene Reconstruction with Balanced Visual and Geometric Qualitycited by 0
  4. 2026OpenFlyScan: A Quality-Guided Aerial Reconstruction System for Consumer Dronescited by 0