Generalized Deep Image to Image Regression

  title={Generalized Deep Image to Image Regression},
  author={Venkataraman Santhanam and Vlad I. Morariu and Larry S. Davis},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
We present a Deep Convolutional Neural Network architecture which serves as a generic image-to-image regressor that can be trained end-to-end without any further machinery. Our proposed architecture, the Recursively Branched Deconvolutional Network (RBDN), develops a cheap multi-context image representation very early on using an efficient recursive branching scheme with extensive parameter sharing and learnable upsampling. This multi-context representation is subjected to a highly non-linear… CONTINUE READING
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  • R. Gross, I. Matthews, J. Cohn, T. Kanade, S. Baker
  • Image Vision Comput., 28(5):807–813, May
  • 2010
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