ML Anthology

Inferring Spatial Layout from a Single Image via Depth-Ordered Grouping

Stella X. Yu, Hao Zhang, Jitendra Malik
CVPRW 2008 pp. 1-7
doi:10.1109/CVPRW.2008.4562977 /cvprw/2008/yu2008cvprw-inferring/

Abstract

Inferring the 3D spatial layout from a single 2D image is a fundamental visual task. We formulate it as a grouping problem where edges are grouped into lines, quadrilaterals, and finally depth-ordered planes. We demonstrate that the 3D structure of planar objects in indoor scenes can be fast and accurately inferred without any learning or indexing.

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Cite

Text

Yu et al. "Inferring Spatial Layout from a Single Image via Depth-Ordered Grouping." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4562977

Markdown

[Yu et al. "Inferring Spatial Layout from a Single Image via Depth-Ordered Grouping." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/yu2008cvprw-inferring/) doi:10.1109/CVPRW.2008.4562977

BibTeX

@inproceedings{yu2008cvprw-inferring,
  title     = {{Inferring Spatial Layout from a Single Image via Depth-Ordered Grouping}},
  author    = {Yu, Stella X. and Zhang, Hao and Malik, Jitendra},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2008},
  pages     = {1-7},
  doi       = {10.1109/CVPRW.2008.4562977},
  url       = {https://mlanthology.org/cvprw/2008/yu2008cvprw-inferring/}
}