MobileBrick: Building LEGO for 3D Reconstruction on Mobile Devices
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Abstract (arXiv)
High-quality 3D ground-truth shapes are critical for 3D object reconstruction evaluation. However, it is difficult to create a replica of an object in reality, and even 3D reconstructions generated by 3D scanners have artefacts that cause biases in evaluation. To address this issue, we introduce a novel multi-view RGBD dataset captured using a mobile device, which includes highly precise 3D ground-truth annotations for 153 object models featuring a diverse set of 3D structures. We obtain precise 3D ground-truth shape without relying on high-end 3D scanners by utilising LEGO models with known geometry as the 3D structures for image capture. The distinct data modality offered by high-resolution RGB images and low-resolution depth maps captured on a mobile device, when combined with precise 3D geometry annotations, presents a unique opportunity for future research on high-fidelity 3D reconstruction. Furthermore, we evaluate a range of 3D reconstruction algorithms on the proposed dataset. Project page: http://code.active.vision/MobileBrick/
Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 25 of its 41 references that are in the map. First posted on arXiv 3 Mar 2023.
Builds on
25 of 41 references.
References · 25
- 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
- 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
- 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,701
- 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,354
- 2014Depth Map Prediction from a Single Image using a Multi-Scale Deep Networkcited by 1,264
- 2021Volume Rendering of Neural Implicit Surfacescited by 990
- 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 961
- 2021MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereocited by 735
- 2018Open3D: A Modern Library for 3D Data Processingcited by 717
- 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 646
- 2020Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understandingcited by 593
- 2019BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networkscited by 487
13 more
- 2021ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Datacited by 442
- 2021Neural RGB-D Surface Reconstructioncited by 312
- 20203D-FUTURE: 3D Furniture shape with TextUREcited by 306
- 2018Pix3D: Dataset and Methods for Single-Image 3D Shape Modelingcited by 218
- 2020Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotationscited by 155
- 2020Visibility-aware Multi-view Stereo Networkcited by 97
- 2016A Large Dataset of Object Scanscited by 64
- 2019Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimationcited by 61
- 2016SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground Truthcited by 31
- 2022BNV-Fusion: Dense 3D Reconstruction using Bi-level Neural Volume Fusioncited by 29
- 2022Translating a Visual LEGO Manual to a Machine-Executable Plancited by 15
- 2022A Real World Dataset for Multi-view 3D Reconstructioncited by 9
- 2020Multi-Scale Progressive Fusion Learning for Depth Map Super-Resolutioncited by 7
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Citing papers per year: 2023: 4; 2024: 3; 2025: 3; 2026: 5.
15 papers.
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- 2024GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Viewscited by 65
- 2023PoRF: Pose Residual Field for Accurate Neural Surface Reconstructioncited by 19
- 2024BANF: Band-limited Neural Fields for Levels of Detail Reconstructioncited by 10
- 2023DiViNeT: 3D Reconstruction from Disparate Views via Neural Template Regularizationcited by 7
- 2025SurfaceSplat: Connecting Surface Reconstruction and Gaussian Splattingcited by 5
- 2024Learning to Build by Building Your Own Instructionscited by 3
- 2023Towards Visual Foundational Models of Physical Scenescited by 2
- 2023Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Datasetcited by 1
- 2025LighthouseGS: Indoor Structure-aware 3D Gaussian Splatting for Panorama-Style Mobile Capturescited by 1
- 2025Reconstruction Using the Invisible: Intuition from NIR and Metadata for Enhanced 3D Gaussian Splattingcited by 1
- 2026When 3D Gaussian Splatting Recovers Real Surfacescited by 1
- 2026NeVStereo: A NeRF-Driven NVS-Stereo Architecture for High-Fidelity 3D Taskscited by 0
- 2026When 3D Gaussian Splatting Recovers Real Surfaces30 Aug 2026
- 2026Triangulation-Free Bundle Adjustment with Graduated Non-Convexity for Camera Pose Refinement from Coarse Priors21 Aug 2026
- 2026Stochastic Signed Distance Processes18 Jun 2026
- 2026EvalMVX: A Unified Benchmarking for Neural 3D Reconstruction under Diverse Multiview Setups27 Feb 2026
- 2026NeVStereo: A NeRF-Driven NVS-Stereo Architecture for High-Fidelity 3D Tasks5 Feb 2026
- 2025Reconstruction Using the Invisible: Intuition from NIR and Metadata for Enhanced 3D Gaussian Splatting20 Aug 2025
- 2025SurfaceSplat: Connecting Surface Reconstruction and Gaussian Splatting21 Jul 2025
- 2025LighthouseGS: Indoor Structure-aware 3D Gaussian Splatting for Panorama-Style Mobile Captures8 Jul 2025
- 2024Learning to Build by Building Your Own Instructions1 Oct 2024
- 2024BANF: Band-limited Neural Fields for Levels of Detail Reconstruction19 Apr 2024
- 2024GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views2 Apr 2024
- 2023PoRF: Pose Residual Field for Accurate Neural Surface Reconstruction11 Oct 2023
- 2023Towards Visual Foundational Models of Physical Scenescited by 2
- 2023Towards Visual Foundational Models of Physical Scenes6 Jun 2023
- 2024GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Viewscited by 65
- 2023PoRF: Pose Residual Field for Accurate Neural Surface Reconstructioncited by 19
- 2024BANF: Band-limited Neural Fields for Levels of Detail Reconstructioncited by 10
- 2023DiViNeT: 3D Reconstruction from Disparate Views via Neural Template Regularizationcited by 7
- 2025SurfaceSplat: Connecting Surface Reconstruction and Gaussian Splattingcited by 5
- 2024Learning to Build by Building Your Own Instructionscited by 3
- 2023Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Datasetcited by 1
- 2025LighthouseGS: Indoor Structure-aware 3D Gaussian Splatting for Panorama-Style Mobile Capturescited by 1
- 2025Reconstruction Using the Invisible: Intuition from NIR and Metadata for Enhanced 3D Gaussian Splattingcited by 1
- 2026When 3D Gaussian Splatting Recovers Real Surfacescited by 1
- 2026NeVStereo: A NeRF-Driven NVS-Stereo Architecture for High-Fidelity 3D Taskscited by 0
- 2026EvalMVX: A Unified Benchmarking for Neural 3D Reconstruction under Diverse Multiview Setupscited by 0
12 most cited of 14 All 14 (JSON)
- 2026When 3D Gaussian Splatting Recovers Real Surfaces30 Aug 2026
- 2026Triangulation-Free Bundle Adjustment with Graduated Non-Convexity for Camera Pose Refinement from Coarse Priors21 Aug 2026
- 2026Stochastic Signed Distance Processes18 Jun 2026
- 2026EvalMVX: A Unified Benchmarking for Neural 3D Reconstruction under Diverse Multiview Setups27 Feb 2026
- 2026NeVStereo: A NeRF-Driven NVS-Stereo Architecture for High-Fidelity 3D Tasks5 Feb 2026
- 2025Reconstruction Using the Invisible: Intuition from NIR and Metadata for Enhanced 3D Gaussian Splatting20 Aug 2025
- 2025SurfaceSplat: Connecting Surface Reconstruction and Gaussian Splatting21 Jul 2025
- 2025LighthouseGS: Indoor Structure-aware 3D Gaussian Splatting for Panorama-Style Mobile Captures8 Jul 2025
- 2024Learning to Build by Building Your Own Instructions1 Oct 2024
- 2024BANF: Band-limited Neural Fields for Levels of Detail Reconstruction19 Apr 2024
- 2024GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views2 Apr 2024
- 2023PoRF: Pose Residual Field for Accurate Neural Surface Reconstruction11 Oct 2023
12 newest of 14 All 14 (JSON)