mlsanityData to 7 Oct 2026

Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image

arXiv 2104.07986 ↗First posted 16 Apr 2021cs.CVcited by 7

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Abstract (arXiv)

Single-image room layout reconstruction aims to reconstruct the enclosed 3D structure of a room from a single image. Most previous work relies on the cuboid-shape prior. This paper considers a more general indoor assumption, i.e., the room layout consists of a single ceiling, a single floor, and several vertical walls. To this end, we first employ Convolutional Neural Networks to detect planes and vertical lines between adjacent walls. Meanwhile, estimating the 3D parameters for each plane. Then, a simple yet effective geometric reasoning method is adopted to achieve room layout reconstruction. Furthermore, we optimize the 3D plane parameters to reconstruct a geometrically consistent room layout between planes and lines. The experimental results on public datasets validate the effectiveness and efficiency of our method.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 25 of its 48 references that are in the map. First posted on arXiv 16 Apr 2021.

Builds on

25 of 48 references.

References · 25

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13 more
  1. 2019End-to-End Wireframe Parsingcited by 72
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  3. 2018DuLa-Net: A Dual-Projection Network for Estimating Room Layouts from a Single RGB Panoramacited by 67
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  8. 2017Physics Inspired Optimization on Semantic Transfer Features: An Alternative Method for Room Layout Estimationcited by 29
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  11. 2020GeoLayout: Geometry Driven Room Layout Estimation Based on Depth Maps of Planescited by 12
  12. 2019Thinking Outside the Box: Generation of Unconstrained 3D Room Layoutscited by 10
  13. 2019Smart Hypothesis Generation for Efficient and Robust Room Layout Estimationcited by 10

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Cited by year

Citing papers per year: 2022: 4; 2023: 1; 2024: 1; 2025: 1.

7 papers.