Generating Images with Perceptual Similarity Metrics based on Deep Networks

@inproceedings{Dosovitskiy2016GeneratingIW,
  title={Generating Images with Perceptual Similarity Metrics based on Deep Networks},
  author={Alexey Dosovitskiy and Thomas Brox},
  booktitle={NIPS},
  year={2016}
}
Discriminator architecture is shown in Figure 1 . In our setup the job of the discriminator is to analyze the local statistics of images. Therefore, after five convolutional layers with occasional stride we perform global average pooling. The result is processed by two fully connected layers, followed by a 2-way softmax. We perform 50% dropout after the global average pooling layer and the first fully connected layer. 

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