• DOI:10.1109/CVPR.2015.7298652
Corpus ID: 9363077

Designing deep networks for surface normal estimation

@article{Wang2015DesigningDN,
  title={Designing deep networks for surface normal estimation},
  author={X. Wang and David F. Fouhey and A. Gupta},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2015},
  pages={539-547}
}

X. Wang, David F. Fouhey, A. Gupta

Published 2015

Computer Science

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

In the past few years, convolutional neural nets (CNN) have shown incredible promise for learning visual representations. In this paper, we use CNNs for the task of predicting surface normals from a single image. But what is the right architecture? We propose to build upon the decades of hard work in 3D scene understanding to design a new CNN architecture for the task of surface normal estimation. We show that incorporating several constraints (man-made, Manhattan world) and meaningful… CONTINUE READING

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