Towards High-Fidelity Single-view Holistic Reconstruction of Indoor Scenes
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Abstract (arXiv)
We present a new framework to reconstruct holistic 3D indoor scenes including both room background and indoor objects from single-view images. Existing methods can only produce 3D shapes of indoor objects with limited geometry quality because of the heavy occlusion of indoor scenes. To solve this, we propose an instance-aligned implicit function (InstPIFu) for detailed object reconstruction. Combining with instance-aligned attention module, our method is empowered to decouple mixed local features toward the occluded instances. Additionally, unlike previous methods that simply represents the room background as a 3D bounding box, depth map or a set of planes, we recover the fine geometry of the background via implicit representation. Extensive experiments on the SUN RGB-D, Pix3D, 3D-FUTURE, and 3D-FRONT datasets demonstrate that our method outperforms existing approaches in both background and foreground object reconstruction. Our code and model will be made publicly available.
Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Builds on 49 of its 58 references that are in the map. First posted on arXiv 18 Jul 2022.
Builds on
49 of 58 references.
References · 49
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37 more
- 2020AdaBins: Depth Estimation using Adaptive Binscited by 596
- 20163D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstructioncited by 587
- 2018AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generationcited by 539
- 2017Neural 3D Mesh Renderercited by 437
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- 2016OctNet: Learning Deep 3D Representations at High Resolutionscited by 340
- 2019DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstructioncited by 332
- 20203D-FUTURE: 3D Furniture shape with TextUREcited by 306
- 2018Pix3D: Dataset and Methods for Single-Image 3D Shape Modelingcited by 218
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- 2016Learning Shape Abstractions by Assembling Volumetric Primitivescited by 181
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- 2019Superquadrics Revisited: Learning 3D Shape Parsing beyond Cuboidscited by 123
- 2019Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networkscited by 106
- 2018PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Imagecited by 105
- 2019Learning elementary structures for 3D shape generation and matchingcited by 98
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Citing papers per year: 2022: 2; 2023: 6; 2024: 12; 2025: 9; 2026: 14.
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