Monocular Depth Estimation Using Neural Regression Forest

@article{Roy2016MonocularDE,
  title={Monocular Depth Estimation Using Neural Regression Forest},
  author={Anirban Roy and Sinisa Todorovic},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={5506-5514}
}
This paper presents a novel deep architecture, called neural regression forest (NRF), for depth estimation from a single image. NRF combines random forests and convolutional neural networks (CNNs). Scanning windows extracted from the image represent samples which are passed down the trees of NRF for predicting their depth. At every tree node, the sample is filtered with a CNN associated with that node. Results of the convolutional filtering are passed to left and right children nodes, i.e… CONTINUE READING
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