Understanding deep image representations by inverting them

@article{Mahendran2015UnderstandingDI,
  title={Understanding deep image representations by inverting them},
  author={Aravindh Mahendran and Andrea Vedaldi},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2015},
  pages={5188-5196}
}
  • Aravindh Mahendran, A. Vedaldi
  • Published 26 November 2014
  • Computer Science
  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Image representations, from SIFT and Bag of Visual Words to Convolutional Neural Networks (CNNs), are a crucial component of almost any image understanding system. [] Key Method We show that this method can invert representations such as HOG more accurately than recent alternatives while being applicable to CNNs too. We then use this technique to study the inverse of recent state-of-the-art CNN image representations for the first time. Among our findings, we show that several layers in CNNs retain…

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