ML Anthology

Data-Driven 3D Primitives for Single Image Understanding

David F. Fouhey, Abhinav Gupta, Martial Hebert
ICCV 2013
doi:10.1109/ICCV.2013.421 /iccv/2013/fouhey2013iccv-datadriven/

Abstract

What primitives should we use to infer the rich 3D world behind an image? We argue that these primitives should be both visually discriminative and geometrically informative and we present a technique for discovering such primitives. We demonstrate the utility of our primitives by using them to infer 3D surface normals given a single image. Our technique substantially outperforms the state-of-the-art and shows improved cross-dataset performance.

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Cite

Text

Fouhey et al. "Data-Driven 3D Primitives for Single Image Understanding." International Conference on Computer Vision, 2013. doi:10.1109/ICCV.2013.421

Markdown

[Fouhey et al. "Data-Driven 3D Primitives for Single Image Understanding." International Conference on Computer Vision, 2013.](https://mlanthology.org/iccv/2013/fouhey2013iccv-datadriven/) doi:10.1109/ICCV.2013.421

BibTeX

@inproceedings{fouhey2013iccv-datadriven,
  title     = {{Data-Driven 3D Primitives for Single Image Understanding}},
  author    = {Fouhey, David F. and Gupta, Abhinav and Hebert, Martial},
  booktitle = {International Conference on Computer Vision},
  year      = {2013},
  doi       = {10.1109/ICCV.2013.421},
  url       = {https://mlanthology.org/iccv/2013/fouhey2013iccv-datadriven/}
}